To our knowledge, this is the first systematic review focused on the comparison of twins' and singletons' linguistic environments. Limited data emerged from the literature, only seven papers and one book chapter matched the inclusion and exclusion criteria and were included (Lytton et al., 1977; Conway et al., 1980; Bornstein and Ruddy, 1984; Tomasello et al., 1986; Stafford, 1987; Ostfeld et al., 2000; Butler et al., 2003; Thorpe et al., 2003). Within all the studies included, differences were found between the groups. The results generally showed the disadvantaged condition of twins. Twins' mothers talked less to the target child and provided more non-facilitative input of lower complexity. Furthermore, twins' mothers were less responsive and more directive when interacting with their children, involved their children in fewer and shorter JA interactions, and stimulated their children less during book reading. As stated by several authors, the results against twins are likely due to the demands related to the twin situation, the limited attentive resources available, and the mothers' attempt to control the situation to manage two children of the same age (Tomasello et al., 1986; Stafford, 1987; Butler et al., 2003; Thorpe et al., 2003). The demands that entail the management of two children of the same age emerged from interviews conducted by Holditch-Davis et al. (1999).  Compared with singletons' parents, twins' parents experienced higher psychological symptoms and parenting stress (Glazebrook et al., 2004; Olivennes et al., 2005; Lutz et al., 2012; Beer et al., 2013; Wenze et al., 2015; Prino et al., 2016). Moreover, they needed greater resources and more involvement to rear twins (Prino et al., 2016). Less optimal interactions among twins and their parents were found in comparison with singletons' families (Glazebrook et al., 2004; Sutcliffe and Derom, 2006; Anderson et al., 2017). However, there were some conflicting results within and between the studies, and the results against twins were not replicated when employing different computational methods (i.e., twin moms value, twin direct dyadic value, twin direct dyadic + both value, and input directed toward both children simultaneously). A need remains to further confirm the results identified and understand the role of the differences found on the child's linguistic skills with specific computational methods to better understand the relevance of the findings against twins for language development. These findings could draw important theoretical and research conclusions about the linguistic environment's features and the input direction that impact twins' linguistic development (i.e., input addressed to the child individually, to the pair concurrently, or expressed by the mother regardless of direction).

On the other hand, it is noteworthy that the results obtained identified data favoring twins for some variables (i.e., use of extensions, items related to action, self-answers, stock expressions, spontaneous declaratives, questions, topic continuation, attention devices, object references, and number of JA interactions initiated by the mother). However, regarding the use of questions, topic continuation, extensions, items related to action, and attention devices, these results were obtained by comparing two triadic situations and coding input directed toward both children simultaneously (Stafford, 1987). These data showed a non-significant negative correlation with the twins' and singletons' linguistic skills (Stafford, 1987). Although the results showed the favoring condition of twins for these dimensions, input directed toward both children simultaneously did not contribute to the target child's language development. These preliminary findings assume theoretical and research relevance, which needs to be further confirmed.

It is also important to note that seven features of the linguistic environment (number of words/utterances, questions, declaratives, directives, topic continuation utterances, imitation, and acknowledgment) were assessed by more than one study. Of these, the results regarding quantity of words/utterances (with the twin direct dyadic value), questions (with the twin direct dyadic and the twin moms values), declaratives (with the twin direct dyadic value), and directives (with the twin moms value) were uniquely replicated by adopting the same computational method, confirming the disadvantaged condition of twins (Conway et al., 1980; Tomasello et al., 1986; Stafford, 1987; Butler et al., 2003).

It is noteworthy that the differences found among the twins' and singletons' linguistic environment are not exclusively due to the comparison of a triadic and a dyadic interaction. Compared with singletons with siblings, twins showed a disadvantaged linguistic environment (Lytton et al., 1977; Stafford, 1987; Thorpe et al., 2003), which could be due to the fact that two children of the same age have the same dependence degree and similar evolutionary needs that can emerge at different times. This entails great demands on the mothers, who cannot rely on the higher independence of one of the children, which would help to limit the double maternal commitment (Tomasello et al., 1986; Thorpe et al., 2003; Wenze et al., 2015). Moreover, twins' mothers were more likely to address the children as a pair, which is a condition that could limit individual stimulation and impact linguistic development (Thorpe et al., 2003). Lastly, as stated by Thorpe et al. (2003), the occurrence of an older sibling rather than a twin could guarantee more complex communication among siblings and a motivation for the mother to adopt a more sophisticated linguistic pattern to comply with the communicative competence of the older child.

Although the results obtained generally showed the disadvantaged condition of twins, conflicting results were identified within and between the studies, mainly according to the computational method employed. The limited data available and the conflicting and not replicated results do not allow the results to be confirmed nor clear conclusions to be drawn regarding the differences in the linguistic environment of twins and singletons.

#### LIMITATIONS

The current review presents several limitations: First, the results are limited by the reduced number of papers included due to the few studies that comply with the established selection criteria. Second, our review is not a meta-analysis, and this study design does not allow statistical conclusions to be drawn about the results found in the included studies. Lastly, limitations are related to the selection and exclusion criteria used: we excluded those studies that employed measures that—despite the evaluation of the linguistic environment's features—do not provide a clear understanding of the differences among twins and singletons, showing instead composite results of the total environment (Beer et al., 2013; Anderson et al., 2017). Moreover, we selected only studies that compared twins and singletons groups, excluding studies that considered only twins and found results that did not identify disadvantaged linguistic environment's features within the twin population (Barton and Strosberg, 1997; Rendle-Short et al., 2015). Finally, we included only studies published in English, not considering papers published in other languages concerned with the issue, which could provide additional information. The adoption of these selection criteria allowed for a clear identification of the studies concerned with the differences in linguistic environments of twins and singletons, but, on the other hand, did not allow the complexity of the issue to be considered. Other studies that draw conclusions about all the environmental variables involved in linguistic learning would be useful.

## FUTURE DIRECTIONS

First, considering the limited and conflicting data that emerged, other studies with a comparative design would be useful to further explore the linguistic environment's features (i.e., quantity and complexity of linguistic input provided, linguistic features of CDS, maternal responsiveness and directiveness, JA interaction, and book reading) for which were found differences among twins and singletons in the studies included (Lytton et al., 1977; Conway et al., 1980; Bornstein and Ruddy, 1984; Tomasello et al., 1986; Stafford, 1987; Ostfeld et al., 2000; Butler et al., 2003; Thorpe et al., 2003) and that emerged as influencing factors for language development (Conway et al., 1980; Tomasello et al., 1986; Stafford, 1987; Ostfeld et al., 2000; Thorpe et al., 2003). This would allow for clearer conclusions about the preliminary differences within the studies included in the current systematic review and for further highlighting of factors potentially associated with the lower linguistic skills found among twins.

Furthermore, other studies are necessary to better understand the twins' and singletons' differences according to the computational method used, as well as the relation of these differences with the lower linguistic skills found among twins. Specifically, future studies focused on the comparison of the twins' and singletons' linguistic environments should employ the different computational methods highlighted by Tomasello et al. (1986) (i.e., input addressed to the child individually, to the pair concurrently, or expressed by the mother regardless of direction) to clarify the direction of parental input that entails differences in the twins' and singletons' linguistic environments. Moreover, further studies are necessary to explore the association between the linguistic environment's features against twins (emerged with the specific computational method) and the twins' language development, controlling for variables that could influence the results found (e.g., age, gender, birthweight, prematurity, and SES). These findings could assume a theoretical and research relevance to further confirm the results found in the studies included in the current review and to clarify the input and the input directions that influence twins' linguistic skills. It is noteworthy that only five studies included in the present review—which, to our knowledge, are the only ones in the literature—performed statistical analysis between the twins' linguistic environment and the twins' linguistic skills, finding results that confirm the influence of the linguistic environment's features (Conway et al., 1980; Tomasello et al., 1986; Stafford, 1987; Ostfeld et al., 2000; Thorpe et al., 2003).

Moreover, most of the studies compared a triadic and a dyadic situation (Conway et al., 1980; Bornstein and Ruddy, 1984; Tomasello et al., 1986; Ostfeld et al., 2000; Butler et al., 2003), while only three research studies compared twins and singletons with siblings (Lytton et al., 1977; Stafford, 1987; Thorpe et al., 2003). Further studies that adopt this latter methodological solution are necessary to better understand whether the differences found are actually due to the demands associated with the twin situation—as emerged in the studies included in the current review that compared two triadic contexts (Lytton et al., 1977; Stafford, 1987; Thorpe et al., 2003)—and not only to the comparison of a triadic and a dyadic context and thus to the complexities related with triadic interactions.

Considering that the differences among twins and singletons emerged both at the prelinguistic age and until 21 months of age (Bornstein and Ruddy, 1984; Ostfeld et al., 2000; Butler et al., 2003), with no differences found at 36 months (Thorpe et al., 2003), other studies with a longitudinal design that assess the linguistic environment of twins and singletons until at least age 3 could be useful to understand whether the

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disadvantaged condition of twins are sustained or resolved as stated by Thorpe et al. (2003).

Lastly, future studies with a cross-cultural design that explore the association between SES and the linguistic environment of twins would improve the level of knowledge of the phenomenon.

#### AUTHOR CONTRIBUTIONS

TT and LR took overall responsibility for the creation of the framework used in this review and the selection of the papers. TT, LC, AC, and EG searched for the articles discussed in the review. LR and PB supervised the entire work. All authors were involved in the discussion, the writing, and the revision of the manuscript, and they gave the final approval of the version to be published.

between 18 and 35 months of age. Early Child Dev. Care 186, 436–452. doi: 10.1080/03004430.2015.1039529

24 months. J. Speech Lang. Hearing Res. 51, 394–407. doi: 10.1044/1092-4388 (2008/029)

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Trombetta, Brustia, Curti, Caldarera, Gerino and Rollè. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Observing Change Over Time in Strength-Based Parenting and Subjective Wellbeing for Pre-teens and Teens

Lea Waters1 \*, Daniel J. Loton1 , Dawson Grace1 , Rowan Jacques-Hamilton1 and Michael J. Zyphur1,2

1 Centre for Positive Psychology, The University of Melbourne, Melbourne, VIC, Australia, 2 Department of Management and Marketing, The University of Melbourne, Melbourne, VIC, Australia

The focus of this study was on adolescent mental health. More specifically, the relationship between strength-based parenting (SBP) and subjective wellbeing (SWB) during adolescence was examined at three time points over 14 months (N = 202, Mage = 12.97, SDage = 0.91, 48% female). SBP was positively related to life satisfaction and positive affect at each of the three time points, and was negatively related to negative affect. SBP and SWB both declined significantly over time. When examining the causal relationships between SBP and SWB, two different statistical models were applied: latent growth-curve models (LGM) and random-intercept cross-lagged panel models (RI-CLPM). The LGM revealed a strong positive relationship between changes in SBP and SWB. Specifically, this model showed that SBP at one time point predicted adolescent SWB at future time points. However, when the more stringent statistical test was completed through RI-CLPMs, no cross-lagged paths reached significance. Thus, while parenting is a significant predictor of wellbeing for pre-teens and teens in real time, it is not predictive of wellbeing at future time points. Parents, thus, cannot assume that their current levels of SBP are 'banked' by their children to support future wellbeing.  Furthermore, the fact that perceptions of SBP decline in this age bracket suggest that SBP interventions may be helpful in supporting adolescent mental health.

#### Keywords: wellbeing, parenting, strengths, adolescence, pre-teens, teens, positive psychology

#### INTRODUCTION

"A healthy family is necessary for a healthy society" (Shapiro, 2004, p. 27)

The teen, and now increasingly pre-teen, years are characterized by intense changes to a young person's physical development, identity, social life, family relationships, exposure to drugs and alcohol, academic requirements, employment and economic responsibilities (Larson et al., 1996; Singh, 1998; Levy-Warren, 1999; Brown, 2004; Sisk and Foster, 2004; Viner and Taylor, 2007; Andersen and Teicher, 2008; Hussain et al., 2008; Sodha and Margo, 2008; Lerner and Steinberg, 2009; Sodha, 2009). As such, the second decade of

#### Edited by:

Yvette Renee Harris, Miami University, United States

#### Reviewed by:

Sherry L. Edwards, The University of North Carolina at Pembroke, United States Chi-Keung Chan, Hong Kong Shue Yan University, Hong Kong

> \*Correspondence: Lea Waters<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology

Received: 10 November 2018 Accepted: 23 September 2019 Published: 10 October 2019

#### Citation:

Waters L, Loton DJ, Grace D, Jacques-Hamilton R and Zyphur MJ (2019) Observing Change Over Time in Strength-Based Parenting and Subjective Wellbeing for Pre-teens and Teens. Front. Psychol. 10:2273. doi: 10.3389/fpsyg.2019.02273

**104**

life sees a young person needing to build up the psychological, emotional, and social capacities necessary to meet the demands of these changes and grow into adulthood. While these skills and dispositions develop continuously from childhood, adolescence has been recognized as a particularly sensitive developmental period for these skills to be gained (Pfeifer et al., 2011; Somerville, 2013) given the shift to more independence (Feldman and Elliott, 1990), greater life complexity (Crone and Dahl, 2012), the teen brains heightened neuroplasticity (Andersen and Teicher, 2008; Giedd, 2008), and the fact that this is the life phase immediately prior to adulthood/emerging adulthood (Steinberg, 2014). Indeed, Patton et al. (2016) state that adolescence is "a critical phase in life for achieving human potential" (p. 2324) as it is the life stage "in which an individual establishes the social, cultural, emotional, educational, and economic resources to maintain their health and wellbeing across the life course." (p. 2427).

Parents are critical in shaping an adolescent's health and wellbeing (Bruyn et al., 2003; Galambos et al., 2003; National Research Council, 2011; Bøe et al., 2018). Yet, in their review of adolescent health and wellbeing, Patton and his colleagues assert: "given that families and parents remain the most important figures in the lives of most adolescents, the paucity of rigorous research into family influences on adolescent health and wellbeing is a striking knowledge gap" (Patton et al., 2016, p. 2432). Adding to the critique of Patton et al., parenting research has been criticized for not adequately studying how parent–child dynamics change over time (Holden and Miller, 1999; Rimehaug et al., 2011) and for having a deficit focus that has concentrated on effects of negative parenting factors (e.g., parent addiction, violence, mental illness, or neglect) at the expense of understanding the effects of positive parenting factors (e.g., compassion, strengths, emotional atonement) (Sheridan and Burt, 2009; Conoley et al., 2015; Waters and Sun, 2016).

The current study focuses on mental health outcomes for adolescents and sits within the paradigm of positive psychology to explore the dynamic effect of strength-based parenting (SBP) on subjective wellbeing (SWB) in pre-teens and early-to-mid teens across a 3-wave longitudinal study.

#### Youth Wellbeing

Research shows that the greatest risk for developing mental illness occurs in the second decade of life (Costello et al., 2003; Slade et al., 2009; Kieling et al., 2011; De Girolamo et al., 2012; Schwartz et al., 2012; Eyre and Thapar, 2014; Patton et al., 2014). Costello et al. (2011) found that there is an increase in rates of panic disorder, agoraphobia, substance use disorders and depression from childhood to adolescence.1 Kessler et al. (2001) epidemiological research revealed a rise from 1% depression in the population under age 12 to 17–25% of the population by the end of adolescence. In early adolescence, epidemiological research shows that mental disorders sit around 10% (10.9%, Anselmi et al., 2010; 9.8%, Frigerio et al., 2009) but rise to 13.4–21.8% in mid to late adolescence (Costello et al., 2011; Polanczyk et al., 2015).

Epidemiological data from Costello et al. (2003, 2011) revealed the most common diagnoses in adolescents to be substance abuse disorders (12.1%), anxiety disorders (10.7%), depressive disorders (6.1%) and behavioral/spectrum disorders (e.g., conduct disorder, oppositional defiant disorder, attentiondeficit hyperactivity disorder; 3–4%). The World Health Organization (2014) lists depression as the number one cause of illness in adolescence and according to Andersen and Teicher (2008) "depression emerges with force and frequency in adolescence" (p.183). Tragically, suicide is a leading cause of death among teenagers worldwide (Hawton et al., 2012).

Naturally, the question has arisen as to whether the prevalence of mental illness has increased over the decades. The evidence is mixed, and while some researchers have found no evidence for change (Costello et al., 2006), the majority of studies find mental illness has increased (Rutter and Smith, 1995; Collishaw et al., 2004, 2010). For example, in the United States of America (USA), Twenge's research has been convincing in showing that mental illness in adolescents and early adults has increased over the generations. For example, Twenge et al. (2010) analyzed generational comparisons using the Minnesota Multiphasic Personality Inventory (MMPI) across college students from 1938 to 2007 (N = 63,706) and across high school students from 1951 to 2002 (N = 13,870) and found that fives time as many of the youth from the later cohorts scored above common cut-offs for psychopathology than compared to the earlier generations.

In another study of generational comparisons across high school and college cohorts from a 1980–1990 cohort to a 2000– 2010 cohort (N = 6.9 million), Twenge et al. (2015) found that the 2010 cohort were twice as likely to report symptoms of mental illness than teens in 1980s. The more recent cohorts also reported greater trouble sleeping, more feelings of being overwhelmed and were twice as likely to have seen a professional for mental health issues. College students from the later decades were more likely to report feeling overwhelmed and to believe they were below average in mental health compared to earlier generations of college students. The suicide rate dropped from 1991 to 2011 but the researchers suggested "subtle symptoms of depression became more prevalent even as some overt indicators of depression became less prevalent" (p. 437).

Finally, Twenge et al. (2018) used two national data sets from 2010 to 2015 to study if there were any shifts in depression, suicidal-outcomes (e.g., making a plan, attempting suicide) and suicide for American adolescents (N = 506,820). The researchers found that depression increased by 33%, suiciderelated outcomes rose by 15% and suicide rose by 31%. These increases in mental health issues were consistent across race/ethnicity, SES, region, and age/grade. However, there were gender effects with females showing greater increases than males.

These trends in the USA are similar those in the United Kingdom (UK) as shown by Collishaw and his colleagues who have conducted a number of independent cross-cohort comparisons of adolescent mental illness in the UK. In one study, Collishaw et al. (2004) compared levels of depressed mood, anxiety and fearfulness (as assessed by parents) in 15/16-year

1 It is important to note that Costello et al. (2011) found a decrease in separation anxiety disorder and attention-deficit hyperactivity disorder from childhood into the teen years.

olds and found a substantial increase from 1986 to 1999. Indeed, the proportion of parents reporting mental health symptoms increased by 70% between 1986 and 1999. In a later study, Collishaw et al. (2010) found increases in symptoms of anxiety and depression from 1986 to 2006 based on youth self-report with twice as many adolescents reporting five or more symptoms of anxiety or depression in 2006 compared to 1986 (15% vs. 7%). Other UK researchers report similar findings and Sweeting et al. (2009) identified that the number of young people meeting established GHQ 'case criteria' almost doubled for Scottish boys and more than doubled for Scottish girls between 1987 and 2006.

In 2015, Collishaw broadened his research sample beyond the UK to look at international trends arising in UK, Finland, the Netherlands and other Nordic countries from 1977– 2011. Data across 21 studies revealed that clinical diagnosis and treatment of adolescent psychiatric disorders, problems and antisocial behavior increased in recent decades. Another international study conducted by Bor et al. (2014) examined long-term time trends (>10 years) in mental health problems for adolescents across seven countries (Finland, Iceland, Sweden, Scotland, UK, USA, and China) and concluded that "The burden of externalizing problems appears to be stable. . . However, the findings for internalizing problems suggest an increasing symptom burden in recent cohorts of adolescents, especially girls" (p.614).

#### Strengths and Youth Wellbeing

It is evident from the data above, that efforts are needed to assist adolescents to build up their wellbeing. One factor that has been shown to be significantly, positively related to wellbeing in young people is that of strengths (Proctor et al., 2011; Suldo et al., 2014). Govindji and Linley (2007) define strengths as "the things you are able to do well or do best" (p. 146). Research into strengths builds upon earlier humanistic psychological research into personality, abilities, self-actualization, virtues and character (Kristjánsson, 2012).

Strengths are one's capacities for excellence and talent, together with one's positive personality traits that play out in persistent patterns of person-environment interaction including one's thoughts, actions and activities (Peterson and Seligman, 2004; Biswas-Diener et al., 2017; Waters, 2017). Strengths provide a person with a sense of energy and efficacy and are used to support one's goals, values and growth (Peterson and Seligman, 2004; Linley et al., 2010).

The scientific study of strengths is a growing body of research (Donaldson et al., 2015) and large-scale bibliometric analyses of the positive psychological literature by Rusk and Waters (2015) demonstrated that the study of strengths has grown considerably in scientific interest since 1992. Indeed, it is the highest growing topic within the field (other rising topics include life satisfaction, positive affect, self-determination and optimism) (Rusk and Waters, 2015).

To date there have been two broad approaches used in the study of strengths. The first approach, a content approach, focuses the types of strengths that people have. This approach has spawned the development of various strengths frameworks and assessments outlining a range of different strengths be they moral qualities (e.g., kindness, courage) (Peterson and Seligman, 2004; see the Values in Action Survey2 ), natural talents combined with knowledge and skills (e.g., maximizer, adaptable; Rath, 2007; see StrengthsFinder3 ) or qualities that are energizing and allow for optimal functioning (e.g., authenticity, narrator; Linley et al., 2010; see Realise24 ).

The second approach, the process approach, moves away from categorizing types of strengths and instead considers the underlying processes that are used to develop strengths. Govindji and Linley (2007), for example, focus their research on developing strengths through two key processes: (1) strength knowledge which they define as a person's "awareness and recognition of their strengths" (p. 146), and (2); and strengths use, which is defined as the extent to which individuals "use their strengths in a variety of settings" (p. 147). Recently, Biswas-Diener et al. (2017) called for a third element beyond knowledge and use to be included in the process-approach to strengths, that of strengths development.

In adult samples (Park, 2004) and youth samples (Park and Peterson, 2006a), knowledge and use of certain character strengths (hope, love, gratitude, and zest) have been associated with greater life satisfaction and, furthermore, the same strengths in parents predict greater LS in their children (Park and Peterson, 2006b). In a meta-analysis of 14 articles (29 effect sizes) on character strength interventions in adult and adolescent samples, Schutte and Malouff (2018) identified significant relationships between knowing and using one's strengths with life satisfaction (weighted Hedges' g of 0.42) and positive affect (weighted Hedges' g of 0.32).

Youth samples show significant relationships between strengths and SWB. For example, in the United States, Suldo et al. (2014) studied the impact of a 10-week school-based wellness-intervention embedded with strengths in pre-teens (aged 10–12) and found significant improvements in life satisfaction after the program. In a sample of 12–14 year-olds in the UK, Proctor et al. (2011) found increases in life satisfaction following a 24-lessons 'Strengths Gym' program. Moving up to older teens and early adults, a study in China found that college students who undertook an 18-week elective course on strengths showed statistically higher levels of life satisfaction after the course than before, and compared to those who did not complete the course (Duan et al., 2014).

The meta-analysis and youth studies cited above show that strengths interventions increase SWB and life satisfaction and, thus, offer a promising route to mental health for teenagers. However, not every young person has the good fortune to participate in a strengths-intervention at school or college and, thus, other more naturally occurring opportunities that build strengths in young people need to be explored.

To this end, research shows that one powerful way to build strengths in a young person is through the strengths feedback they receive from others in their everyday life. For example, Spreitzer et al. (2009) found that when teenagers receive strengths

2www.viacharacter.org

3www.gallupstrengthscenter.com

4 blog.cappeu.com/realise2/

feedback from teachers, coaches, bosses, friends and family it boosts their wellbeing. Importantly, this research showed that strengths feedback from both professional (teachers, coaches, bosses) and personal sources (family and friends) was more important than strengths feedback from professional sources alone, suggesting that parents play an important role in teens learning about their strengths.

The finding that other people can be even more accurate than the self at predicting certain trait-relevant behaviors and abilities (Vazire and Mehl, 2008; Vazire, 2010) suggests that others sometimes know us better than we know ourselves. In particular, few experiences in life rival the extensive insight gained about another human being than that of a parent raising their child. As parents have a myriad of daily opportunities to notice which situations and activities their child enjoys, is energized by and performs well in, they are uniquely placed to provide feedback to their teenager about his or her strengths.

#### Parenting and Youth Wellbeing: Strength-Based Parenting

Parenting has been a topic of empirical psychological inquiry since the 1960's and over the past 50+ years researchers have examined a range of ways in which parenting affects a child's mental health, adjustment, brain development, and trajectory into adulthood (for reviews see Steinberg, 2001; Mejia et al., 2012).

Historically, the research has focused on the effects of harmful parenting with studies investigating the impact of parental control, punishment, coldness, neglect, violence, conflict, addiction and mental illness on child and teen outcomes (Steinberg, 1987; Erel and Burman, 1995; Lovejoy et al., 2000; Caprara et al., 2002; Barnard and McKeganey, 2004; Dubowitz and Bennet, 2007; Ma et al., 2012). The impact of such parenting has been shown to lead to increased risk of psychopathology, suicidal ideation, substance abuse, delinquency, aggression, externalizing disorders, teen pregnancy and criminal behavior as well as deficits in social and emotional functioning (Kinard and Klerman, 1980; Baumrind, 1991a; McCloskey et al., 1995; Kaplan et al., 1999; Mejia et al., 2012). Beyond the focus on negative parental states (e.g., addiction, mental illness) and negative parenting practices (e.g., punishment, discipline, violence, neglect), environmental adversities and family level adversities such as poverty, poor education levels of parents and family stress have also been shown to be related to negative outcomes for adolescents including peer problems, emotional and conduct problems, inattention, mental health problems and psychiatric disorder (Bøe et al., 2012, 2018).

Prospective and retrospective studies have shown that negative parenting during adolescence leads to a raft of harmful outcomes not only in one's youth but also through into adult life including poorer adjustment to college, marriage, and to becoming parents themselves, as well as greater risk of heart attack, alcoholism, and obesity (Holmes and Robins, 1988; Mullen et al., 1999; Vaillant and Mukamal, 2001; Willinger et al., 2005; Schnuck and Handal, 2011; Bentley and Widom, 2012). Sadly, longitudinal research shows that adults with a history of parental maltreatment in their childhood are three times more likely to have depression and suicidality (Brown et al., 1999).

The research above has motivated an early intervention approach through the design of parenting programs used with at-risk families. One such example is the Family Strengthening Program, a strength-based program for families in crisis and for whom child safety concerns have been identified. This program involves therapists working with parents to teach them solution-focused strategies and unearth the assets within the family that can be used to create safer, healthier patterns. The Family Strengthening Program been shown to improve family safety, family health, family interaction, and child wellbeing (Katsikitis et al., 2013).

In addition to working with families at risk of harm, programs have also been designed to assist parents who may have high levels of parental stressors due to raising children who have challenges such as autism, developmental disabilities, intellectual disabilities, anxiety disorders and conduct disorders (Feldman, 1994; McConachie and Diggle, 2007; Plant and Sanders, 2007; Cartwright-Hatton et al., 2011). The Positive Parenting Program (Triple P) is one successful example that has been utilized in families with children who have behavioral, emotional, and/or developmental problems (Sanders et al., 2000). This program teaches parents how to praise pro-social behavior, minimize coercion and reduce opportunities for problem behavior (e.g., by providing ground rules). The meta-analysis of de Graaf et al. (2008) found the Triple P parenting program successfully reduces disruptive behaviors in children.

Other strength-based movements in family therapy include 'family centered services' (Dunst and Deal, 1994) and 'resilient families' (McCubbin et al., 1999; Shortt et al., 2007) both of which employ positive processes to reduce negative outcomes for families undergoing adversity and/or crisis.

Looking at the above research, it is no surprise to learn that the parenting literature has been criticized for its bias toward studying negative factors in terms of the type of families studied (families in distress/dysfunction/crisis; families at-risk, low SES families) and in terms the outcomes investigated (e.g., mental illness, substance abuse, conduct disorders, behavioral disorders). The programs used, while positively oriented, are designed to focus upon family problems (e.g., behavioral disorders) and are measured in terms of the ability to reduce negative outcomes (e.g., conduct disorders). Indeed, according to Shapiro (2004), much of the existing research in parenting is characterized by "one-sided and negative views of family process" (p. 33). In line with this, Sheridan and Burt (2009) assert that "Most research in children and families maintains a deficit focus; it concentrates more on the role of risk factors than assets." (p.552). Similarly, Katsikitis et al. (2014) argue that "Much of the focus of mother-daughter relationships in the literature has been on strategies to manage and deal with negative adolescent behavior" (p. 1).

While a great deal is now known about the adverse impacts of being raised with parental abuse, neglect, mental illness, conflict and the like; and while we have learnt about the impact that positive parenting approaches can have on ameliorating negative outcomes, such as harm in at-risk families and conduct issues in certain sub-samples of children, surprisingly little is known

about how to support parenting approaches that create positive outcomes for mainstream families who are not at risk and are not dealing with adversities such as poverty or children with challenging behaviors. Yet, when considering Seligman's (1999) call, that psychology should be able to help document the factors that promote flourishing families (not just support struggling families), it is time for parenting research to study the ways in which we can enhance positive outcomes in everyday families. Given that mainstream families (i.e., families who do not meet the clinical levels for dysfunction or pathology) represent the biggest proportion of families in society, Seligman's call motivates us to apply parenting research to the whole community and not just those with difficulties.

One pioneer in the application of positive parenting in non-clinical families is Steinberg who, together with his colleagues, has been studying the effect of autonomy-granting parenting since the 1970's in everyday families across multiple cultures5 (Steinberg et al., 1992; Gray and Steinberg, 1999; Steinberg, 2001; Steinberg and Morris, 2001; Steinberg, 2014). Autonomy-granting parenting refers to the extent to which parents allow teens to develop their own opinions and beliefs and is characterized by three parental elements: warmth, boundaries/firmness, and autonomy granting (Steinberg, 2000). Autonomy-granting parenting has been related a host of beneficial outcomes for children and teens including higher self-esteem, social-confidence, subjective wellbeing, self-reliance, achievement motivation and school grades (for a review see Steinberg, 2001). Steinberg's work has long shown us the benefits of positive parenting.

Other positively oriented research can be found in the USA with Baumrind's work on authoritative parenting, defined as warm and firm (Baumrind, 1991b) and the research by Conger et al. (1992) who showed that positive behavior in mothers (e.g., nurturing and involvement) predicted school performance, self-confidence and peer relationships. In Australia, Havighurst and her colleagues have found that when parents are taught how to emotionally tune into their children they are more skilled at discussing causes and consequences of emotions and this leads to fewer internalizing issues with their children (Havighurst et al., 2010; Kehoe et al., 2013). In another Australian study, a longitudinal prospective study that tested the relationship between parent communication and brain development showed that positive parent communication (defined as a pattern of communication where the parent is approving, validating, affectionate, humorous, happy, pleasant, and caring) was associated with beneficial brain growth that enhances capacity for learning, decision-making, social skills, and emotional functioning (Whittle et al., 2014). As part of the Bergen Child Study in Norway, Bøe et al. (2014) found that affirmative parenting practices such as love, affection, praise, rewarding and respect as well as giving help and support when the adolescent is stressed (Last et al., 2012) were inversely related to externalizing problems, such as conduct problems and hyperactivity-inattention, together with internalizing problems, such as peer problems and emotional problems, in 11–13 years olds. Moreover, these positive parenting practices together with the parent's own emotional wellbeing, mediated the relationship between the family's socio-economic status and the degree to which the early adolescents were reporting symptoms of externalizing and internalizing disorders. Finally, a two-wave retrospective study in the UK on well-being in midlife women showed that the effects of positive parenting from childhood persisted into adulthood, with higher levels of parental care being associated with higher psychological well-being in mid-life (Huppert et al., 2010).

Although the last five decades have tipped more to the deficit end of parenting research, there have been pockets of positively oriented research as identified above. More recently, the advent of positive psychology, through its umbrella effect of gathering together positively oriented science into an aligned movement (Rusk and Waters, 2013, 2015) has provided the impetus and platform for a larger group of researchers to study factors that create thriving families (Shapiro, 2004; Sheridan et al., 2004; Katsikitis et al., 2013; Waters, 2017). Indeed, positive psychology, with its appreciative outlook on human virtue, resilience and potential, provides parenting researchers with a broad canvas upon which to explore the positive and pro-social side of family life. Several new strands of positive psychology research are being applied in parenting and family research both in clinical/at risk families and mainstream families. These strands of research include mindful parenting (Dumas, 2005; Geurtzen et al., 2015; Waters, 2016), family centered positive psychology (Sheridan et al., 2004; Sheridan and Burt, 2009), positive family therapy (Shapiro, 2004; Conoley et al., 2015), empathy (Farrant et al., 2011), compassion-focused parenting (Neff and McGehee, 2010; Kirby, 2017; Kirby and Baldwin, 2018) and SBP (Waters, 2015a,b, 2017; Waters and Sun, 2016; Jach et al., 2017; Loton and Waters, 2017; Waters et al., 2019).

Some of these strands of inquiry are still in the conceptual phase (e.g., family centered positive psychology, positive family therapy) and most are in the early stages of empirical research, which is to be expected given that positive psychology is still a relatively new field. At this stage in time, SBP has the highest number of peer reviewed empirical publications of the positive psychology parenting topics outlined above and is the focus of the current three-wave field study.

Waters (2015a) defined SBP as an approach to parenting that "deliberately identifies and cultivate positive states, positive processes and positive qualities in children" (p. 690). Rather than take a content approach to strengths, SBP follows the process approach in that it focuses on how parents can help their children develop and improve their strengths, regardless of what the type of strength is (Waters, 2017). The 'cultivate' element of the SBP definition includes both the 'use and develop' aspects of a process model of strengths and, thus aligns with both Govindji and Linley's (2007) process model (knowledge and use) as well as the model of Biswas-Diener et al. (2017; identify-usedevelopment). SBP has been found to be a distinct parenting construct to autonomy-granting parenting (Waters, 2015b; Loton and Waters, 2017).

5Note: autonomy granting parenting has also been studied in at risk and troubled youth.

The effects of SBP on children, teenagers and parents have been examined using a range of different methods including survey research, vignette studies, dyadic studies, intervention studies, longitudinal studies, and panel designs in sample sizes ranging from 100 to over 11,300 (Waters, 2015a,b; Jach et al., 2017; Loton and Waters, 2017; Sagkal and Özdemir, 2019 ˘ ). Research on SBP has identified two overarching findings: (1) SBP is a protective factor that is inversely related to anxiety, depression, stress, and negative emotions; and (2) SBP is an enhancing factor that is positively related to life satisfaction, self-confidence, subjective wellbeing, positive emotions, and academic grades. The relationship between SBP and youth mental health is mediated by engagement, self-efficacy, persistence and mental toughness (Loton and Waters, 2017; Sagkal and Özdemir, ˘ 2019; Waters et al., 2019). Mindset has been found moderate the relationship between SBP and strength use in teens (Jach et al., 2017). Research in the effects of SBP on the mental health of parents shows that SBP boosts parental self-efficacy and positive emotions in the parents (Waters and Sun, 2016). Research in the effects of SBP on the family level happiness shows that SBP interventions raise happiness in families (Waters, in press).

#### Parental Stability Over Time

Given the significant influence a parent has on their pre-teen and teen's wellbeing, the question of the degree to which a parent displays consistent parenting over time is an important one.

Currently, there are two competing viewpoints held as to the temporal stability of parenting. The invariant viewpoint has historically been the most dominant in the literature and holds that parenting is trait-like and, thus, stable over time. As an advocate of the invariant approach, Maccoby (1984) argued that "We can assume that the family system, like any system, has self-stabilizing properties [horizontal ellipsis]. Families stabilize around habitual patterns of interaction; thus, there is continuity over time in the familial forces" (p. 326). The assumption of temporal consistency in parenting allows researchers to assume that child-rearing approaches assessed at one point in time are a stable reflection of future parenting and can, thus, be used to predict child outcomes over time (e.g., Baumrind, 1991a; Maccoby, 1992; Steinberg et al., 1994; Holden, 1997).

An alternate school of thought characterizes parenting as consistent and mutable, arguing that parental behavior is influenced not only by parent traits but also by the changes in needs and behaviors of the child over time6 (Bornstein et al., 2008). While recognizing that a certain proportion of parenting is constant over time, this approach also explores the adjustments and changes that parents make in their approaches as their children grow. To this end, Madigan et al. (2016) assert that "It is necessary for the field to move beyond an exclusive focus on stability" (p. 122).

Holden and Miller (1999) conducted a meta-analysis on studies that had assessed parenting invariance-stability in infancy and childhood (babies: 0 months to 11 months/infants: 1– 2 years/children: 3–11)7 , and found that maternal behavior was moderately enduring over time (r = 0.45) but was also "a moving picture of parent-child interaction" (p. 243). In other words, parenting is both stable and changeable. In another test of variance-invariance in maternal patterns during in infancy and early childhood, Madigan et al. (2016) conducted a three-wave study over 36 months and concluded that stability and variability co-exist in parenting during the young years.

When it comes to the pre-teen and early-teen years, research shows the same pattern of variance-invariance and a notable trend toward more negative parenting styles as compared to earlier childhood years (Collins, 1990; Rimehaug et al., 2011). A particular pattern identified in the research is that the decline in parenting is most prominent during early adolescence where control, conflict, power, prohibition, and secrecy rise, while support, knowledge about the child, and closeness decrease (Stattin and Klackenberg, 1992; McGue et al., 2005; De Goede et al., 2009; Keijsers et al., 2010; Keijsers and Poulin, 2013). According to Levy-Warren (1999), this dip in early adolescence is likely to be due to the teen's drive for autonomy and individuation which leads to increases in conflict and parent–child distance (Levy-Warren, 1999).

The pattern of negative changes in the parent-teen relationship alters as the teen becomes older and the parent-child relationship has been re-negotiated to one of power symmetry, where research shows closeness, respect, and trust between teen and parent rises while conflict and control diminish in the last teen years (Smollar and Youniss, 1985; Steinberg, 2001; De Goede et al., 2009).

A quick glance over the parenting variables examined above such as control, prohibition, and power, reveal a prevalence of negatively oriented constructs being tested in temporal teenparent studies. But what of the stability of more positively oriented constructs of parenting? Does positive parenting stand the test of time or does it also take a 'nose dive' in the teenage years? Here, it is fair to say, the answer is still unclear as there have been few studies exploring the changes to positive aspects of parenting over time. The small amount of research that has been done, however, suggests that positive aspects of parenting decline during the pre-teen and early teen years. This has been found for parental warmth (McGue et al., 2005; Rodríguez et al., 20148 ; Walkner and Rueter, 2014), parental closeness (Walkner and Rueter, 2014), parental support (Hafen and Laursen, 2009), as well as parental involvement, closeness and regard (McGue et al., 2005) – all of which decrease in pre-teen and teen years.

No studies have yet examined naturalistic change in SBP across time. While SBP has been treated as a trait-like construct in past studies (Waters, 2015b; Waters et al., 2019) it is also possible that SBP, like many other aspects of parenting, changes across the

6The current study focuses on variance-invariance over time but it is also important to note that the stability of parenting has also been examined across contexts, tasks and siblings (see Holden and Miller, 1999; Madigan et al., 2016).

7Note: The large majority of the studies included in Holden and Miller's metaanalysis were of parenting in the first year of a baby's life (45%), followed by studies of parenting from ages 1–3 (32%). This meta-analysis included only four studies that contained teenage sample (7%).

8Rodríguez et al. (2014) found gender differences in parenting. Modest declines in paternal warmth were evident from early to late adolescence, but maternal warmth was high and stable across this time period.

pre-teen and teen years. The reduced knowledge of parents about their teens, together with reduced teen-parent closeness may provide parents with fewer opportunities to see and acknowledge their teen's strengths. Increased conflict between parents and their teens may make it more challenging for parents to see the strengths in their child, and/or may make the teen feel the conflict is occurring because the parents is only seeing their problem behaviors and is not acknowledging their positive qualities. This could result in SBP declining in the pre-teen and early-to-mid teen years. Increased self-doubt in teenagers may also mean that, even if the parent remains constant in their strengthbased approach, the teen is not able to consistently absorb and integrate the positive feedback. For these reasons, and in-line with the research on parenting invariance during the pre-teen and teen years, especially the finding that other positive aspects of parenting decline, it is reasonable to assume that SBP will decline through the pre-teen and into the early teen years.

#### The Current Study

Prior studies of SBP have relied on single-time-point or two-timepoint designs (Waters and Sun, 2016; Sagkal and Özdemir, 2019 ˘ ; Waters et al., 2019). While these studies have usefully identified measurement characteristics, mediating and moderating factors, and wellbeing outcomes of SBP, more research is required to test if SBP naturalistically changes over time and, additionally, how the relationship between SBP and wellbeing changes over time. One means by which researchers can empirically investigate the dynamic causal relationship between SBP and SWB is by observing factors over multiple time points and establishing temporal precedence (McArdle, 2009; Hamaker et al., 2015). That is, whether a change in one variable tends to precede a change in another, which supports separable causal directionality and is one criterion for understanding causality. This study primarily aims to extend research on SBP by examining change in SBP and SWB at three time points over a period of 14 months in a sample of pre-teens and teens. The study is guided by four hypotheses.

Hypothesis One: Consistent with prior studies showing reductions in life satisfaction in teen samples, adolescent SWB is predicted to show a decline over time.

Hypothesis Two: Consistent with past research showing a reduction in positive parenting during the teen years, it is hypothesized that SBP will decline over time.

Hypothesis Three: Over time, adolescents who experience decreases in SBP will also tend to experience decreases in SWB, meaning these factors are likely to change together.

Hypothesis Four: After accounting for within-person stability and auto-regressive effects, changes in SBP will cause concomitant changes in SWB in the form of past SBP predicting future SWB.

#### MATERIALS AND METHODS

#### Sample

The sample for this study comprised students across years 7–9 from a public secondary school in Victoria, Australia. The sample formed part of a three-wave study and two previously published cross-sectional studies have been published from this data set (Jach et al., 2017; Waters et al., 2019). The current paper investigates the causal and longitudinal effect of SBP on SWB, in the sample of students who successfully completed all three waves of the survey.

The school from which the sample was drawn has a socioeconomic index equal to the Australian average, indicating it is representative in terms of socio-educational advantage. Two hundred and two adolescents between the ages of 12–15 completed all three waves of data collection and formed the current sample (Mage = 12.97, SDage = 0.91, 48% female, 49.5% male, 2% preferred not to say and 1 selected 'other' gender). Unequal numbers of participants participated across the year levels (N = 113 or 55.9% Year 7s, N = 39 or 19.3% Year 8s, and N = 50 or 24.8% Year 9s; χ 2 = 47.36, p < 0.001). It is unclear why response rates were lower in years 8 and 9 but it could be due to timetabling issues when the survey was completed in class time. Potential sample bias was analyzed (see Sample Bias Due to Attrition) below with tests comparing participants who completed all three waves, to those only completing one or two. Of the four variables across three points in time, only one variable (PA at time two) was significantly different between responders and non-responders indicating that response bias was not an issue in this sample.

#### Procedure

Students completed a 30-min online survey during school hours across the three time points and their surveys were matched based on a unique ID number. Applying listwise deletion, 15 cases were removed due to missing data. Data collection took place in May, 2016, November, 2016, and July 2017. The average number of days elapsed between data collection waves from baseline to wave 2 was Mdays = 184.77 (SDdays = 9.89) and number of days between wave 2 to wave 3 was Mdays = 241.1 (SDdays = 3.66). The average total time elapsed from baseline to the third wave of measurement was (Mdays = 426.49, SDdays = 8.46, Mmonths = 13.50, SDmonths = 0.50).

All procedures in this study complied with the National Statement on Ethical Conduct in Human Research and were approved by the University of Melbourne's Human Research Ethics Committee, and school Principal. Standing informed consent was provided by parents, through a process of advertising the study in the school newsletter and website prior to data collection, with an option to for their child opt-out. Participating students were also given active 'assent' to withdraw from the study and were advised by the classroom teacher and school Wellbeing Coordinator immediately preceding in-class data collection that the study was voluntary.

#### Measures

#### Strength-Based Parenting Knowledge

The 7-item SBP-knowledge scale (Jach et al., 2017) asks teens to rate the degree to which their parents see and understand their strengths. 'Strengths' here are defined broadly to include "personality, ability, talents and skills." They are non-specific and subjective, that is, particular strengths listed in some strengths taxonomies (e.g., love of learning, kindness,

empathy, perseverance) are not included in the scale. Participants responded to items (e.g., "My parents see the things I do best") on a 7-point scale ranging from 1 (strongly disagree) to 7 (strongly disagree). Scores ranged from 7 to 49.

The SBP knowledge scale has demonstrated strong internal consistency across several studies, with a current omega reliability coefficient of ω = 0.95, 95% CI [0.94,0.96]. The scale has shown discriminant validity from autonomy-granting and responsiveness parental styles, and incremental validity in predicting life satisfaction in teens over and above authoritative parenting (Waters, 2015b). The scale also shows moderate convergence between teen ratings of their parents' strength knowledge and parents' self-reported strength knowledge (Waters, 2015a).

#### Subjective Wellbeing

Following Diener (1984) model of subjective wellbeing, we assessed the three elements of positive affect (PA), negative affect (NA), and life satisfaction (LS). Positive and negative affect were measured using the 10-item shortened Positive and Negative Affect Schedule for Children (Ebesutani et al., 2012). Students rated the extent to which they felt positive affect (e.g., joyful, happy) and negative affect (e.g., miserable, afraid) on a 5-point scale ranging from 1 (very slightly or not at all) to 5 (extremely). Scores ranged from 5 to 50.

Life satisfaction was measured using the 5-item Satisfaction with Life Scale for Children (Gadermann et al., 2010). Participants responded to items (e.g., "In most ways my life is close to the way I would want it to be") on a 5-point scale ranging from 1 (disagree a lot) to 5 (agree a lot). Convergent and discriminant validity has been demonstrated for these three components of subjective wellbeing in several other studies (Gadermann et al., 2010; Ebesutani et al., 2012). Scores ranged from 5 to 25.

#### Data Analysis

Two statistical approaches to model longitudinal data were applied. Both use a structural-equation modeling (SEM) approach with latent variables indicated by survey items, thereby accounting for measurement error in scales. Latent factors also model change that occurs over time by fitting a curve to each participant's scores, in what are commonly termed latent growth curve models (LGM; Duncan and Duncan, 2009), in order to examine univariate change in all study variables (hypothesis One and Two); and relationships between rates of growth between variables over the study period (hypothesis three). A randomintercept cross-lagged panel model (RI-CLPM; Hamaker et al., 2015) was also applied to test for possible within-person causal effects of SBP on PA, NA and LS (hypothesis Four) while controlling for and assessing the degree of between-person stability in the variables over time. As scale ranges vary across SBP and the other measures, we rely on reporting standardized (SD units) effects where suitable.

#### Latent Growth Models

An LGM investigated intra-individual change over time by modeling a latent trajectory for each participant's three repeated measures. Scores at each time point were used as indicators of the trajectory (Raudenbush, 2001; Muthén and Muthén, 2015). With three data points, an LGM is limited to linear trajectories, but this technique can still be a useful way to examine withinperson change and the correlation among change across multiple variables. In the present case, we investigated correlated change in SBP and LS, NA and PA simultaneously. The linear time factor included an additional 50% for the second lag, as the time difference between T2-T3 was approximately 50% longer (9 months vs. 6 months).

#### Random Intercept Cross-Lagged Panel Model

RI-CLPM was to analyze causality between SBP and SWB. According to Hamaker et al. (2015) these models are suitable to non-experimental settings with datasets comprising three repeated measures or more. Like traditional crosslagged panel models, the RI-CLPM construe causality similar to Granger (1988). However, the approach also apportions variance to a latent factor capturing a timeinvariant average around which people's levels on a given measure tend to regress over time. This approach facilitates examination of causal change (i.e., cross-lagged effects) separately to change associated with mean reversion (i.e., autoregression).

Longitudinal studies of life events and SWB highlight the importance of capturing stable within-person predispositions, which form early and are resistant to change in all but drastic events (Diener et al., 2018). The ability of the RI-CLPM to achieve this decomposition has been described by some as arising from separating within- and betweenperson variability (for an example with adolescent parentalrelated data see Keijsers, 2016). However, LGMs also undertake a similar 'multi-level' treatment of change over time by first modeling trajectories for individuals, then considering population distribution characteristics in the sample of these individual trajectories (Raudenbush, 2001). The autoregressive and cross-lagged paths in the RI-CLPM are reflective solely of within-person change, without the influence of betweenperson variance.

Initially, maximum-likelihood (ML) was the chosen estimator, but due to problems with convergence under ML, a Bayesian estimator with uninformative or diffuse prior probabilities was adopted – these priors allow Bayesian and ML results to converge in the long run (Muthén and Asparouhov, 2012). Specifically, under ML the RI-CLPM failed to converge in some cases due to very high latent correlations among betweenperson factors, indicative of strong correlations among stable traits driving stability in the variables. Bayesian estimators are known to perform better than ML under conditions where values are near the edges of their parameter spaces, as is the case here with highly correlated latent factors. For similar issues, Bayesian estimators are also becoming more widely applied in longitudinal analyses (Asparouhov et al., 2018). ML estimation was utilized for nested model tests of measurement and invariance properties. To investigate the

influence of sample size on the key parameters of interest, a post hoc power analysis was undertaken by imputing the Bayesian-derived estimates into Monte Carlo simulations of varied sample sizes.

#### RESULTS

#### Data Cleaning and Preparation

Data cleaning and preparation was undertaken in SPSS and Excel, with MPlus used for all substantive analyses. Data were examined for out-of-range values, survey completion

SBP, Strength-based parenting knowledge. LS, life satisfaction. PA, positive affect. NA, negative affect. Skew, skewness. Kurt, kurtosis. Standard error of skewness = 0.17, standard error of kurtosis = 0.34. ∗ = smallest mode is shown. T denotes the wave of data collection. Total range for SBP is 7–49; NA, PA, and LS from 5 to 25.

times, open-ended comments that suggest spurious responses, duplicate I.P. addresses and/or participants, and missingness. One participant was cut due to a completion time of less than 2 min and many items in neutral. Fifteen cases had almost no items completed and were excluded. Only four other cases demonstrated some missingness, with approximately half the survey items missing in each case. These cases were retained as full-information- ML was utilized. Items were reverse-scored where necessary to consistently measure their underlying factor, and simple scale means calculated.

#### Outliers

Data were screened for outliers. As shown in **Table 1**, univariate (±2 SD of the mean) and multivariate (Mahalanobis Distance, with probability from the Chi-Squared distribution greater than p < 0.001 with df = 12) outliers were identified in distributions of observed scores of the final matched sample (Tabachnick et al., 2001). Relatively few cases were identified as outliers, and a theoretical rationale for excluding univariate and multivariate outliers was not apparent. As such, all were retained.

#### Descriptive Statistics

Distributional characteristics for all variables are reported in **Table 1** and correlations are presented in **Table 2**. Observed score distributions indicate acceptable levels of skewness and kurtosis, with SBP knowledge, LS, and PA somewhat negatively skewed (mean falling on the higher end of the scale), and NA positively skewed (mean falling on the lower end of the scale). A slight decrease in SBP simple scale mean scores was evident as time progressed, probabilistically indistinguishable from zero in T1- T2 (M = −0.11, SD = 1.23, t = −1.24, p = 0.22); a slightly larger and significant decrease from T2-T3 (M = −0.18, SD = 1.20, t = −2.12, p = 0.03); and a significant decline over the full study period (M = −0.29, SD = 1.34, t = −3.02, p = 0.01). Significant correlations were evident between SBP and SWB at all three time points. SBP was positively correlated with LS and PA, and inversely correlated with NA.

SBP, Strength-based parenting knowledge. LS, life satisfaction. PA, positive affect. NA, negative affect. N = 202. T denotes the wave, with T1 being the first measurement interval/baseline. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

#### Sample Bias Due to Attrition

fpsyg-10-02273 October 8, 2019 Time: 12:41 # 10

Returners for all three waves (N = 202) were compared to nonreturners of either time 2 or 3 (N = 380–504 depending on measure). As mental health is known to decline over the teen years, baseline year level was included as a control variable. To retain the benefit of accounting for measurement error, a structural equation model tested the effect of attrition status (a dichotomous predictor) on the continuous latent outcome variables. In this instance, the effect of attrition reflects a probit regression estimate using weighted least squares, while all other estimates reflect linear regression of continuous, latent variables, utilizing full information maximum likelihood to handle missing data.

Results of the attrition analysis are presented in **Table 3**. Students in later year levels had significantly lower cross-sectional SBP, LS, PA and higher NA at T1. In addition, higher baseline year level was associated with lower PA at T2. Only one of the outcomes variables was significantly predicted by attrition status, with students reporting higher life satisfaction at T2 more likely to complete all three waves. Given that this was the only significant difference, across 4 variables across 3 points in time, between responders and non-responders we are confident that the results of the final sample are reflective of the fuller sample at baseline.

#### Measurement and Invariance Testing

Before proceeding to the RI-CLPM, invariance testing was undertaken to ensure measurement properties of the scale were comparable over time. Measurement invariance testing consisted of modeling a latent factor at each wave for each measure, freely covaried and using ML estimation, with measurement properties evaluated against Hu and Bentler's (1999) simulation-based fit indices, with Cheung and Rensvold's (2002) recommendation of a <0.01 change in CFI was used as the key basis for proceeding. **Table 4** presents results of the measurement invariance testing, which was then applied in the RI-CLPM models.

Strength-based parenting had good measurement qualities and retained good fit under scalar invariance. SWL had good

SBP, Strength-based parenting knowledge. LS, life satisfaction. PA, positive affect. NA, negative affect. T denotes the time point. Returners to all three waves of data were dummy coded as '1' and non-returners as '0.' N = 202 participants returned for all three waves.

model fit indices under metric invariance, but fit declined under a scalar invariance, and a partial intercept invariance model was adopted, with LS items 3 and 2 intercepts being freely estimated. Possibly consistent with the more temporally variable nature of emotion, which is itself an indicator of healthy emotional function (Koval et al., 2016), PA and NA both demonstrated poorer invariance properties; and NA also had poorer singlefactor measurement properties. PA had acceptable fit indices but required one factor loading to be freely estimated to retain good fit, and all but one intercept to be freely estimated. NA had poor measurement qualities, but without any very low loading items, or a theoretical rationale for modeling anything but a one-factor solution to the scale, invariance testing was not undertaken. Results of the RI-CLPM including NA should therefore be interpreted with caution. The final measurement models identified in **Table 4** were utilized in the subsequent latent growth and random intercept cross-lagged panel models.

#### Hypotheses One and Two: Latent Growth Curve Model

The LGM provides a robust test of intra-individual change across the sample in SBP and SWB and forms the tests of hypotheses 1–3. As the LGM controls for measurement error by design, simple scale mean scores were used, and to account for the unequal data collection waves an additional 50% of time was included in the time factor in the second lag. A single LGM simultaneously estimated univariate and correlated change in SBP, LS, PA, and NA.

This LGM was initially modeled with ML estimation, which provided good fit (χ 2 (34) = 119.934, p < 0.001; RMSEA.112 [0.091.134]; CFI.922; TLI.849), suggesting a linear curve fit the sample well. However, a non-positive definite matrix made the solution unreliable. As such, a Bayesian estimator with 10000 iterations and diffuse/uninformative priors was adopted, which converged according to acceptable criteria (a posterior scale reduction or PSR < 1.05 for the latter half of iterations). Posterior SD is reported as Standard Error (SE) for Bayesianderived estimates.

#### Hypothesis One

Latent growth-curve models results demonstrate a significant univariate decline in within-person SBP across the time period (unstandardized mean slope factor µSBP−S = −0.12. [−0.19 −0.04], SE/PSD (posterior SD) = 0.04, p < 0.001), thus hypothesis one was supported. Participants starting values also influenced their change over time. Covariances between the intercept and slope factors in the LGM indicate participants who began with initially higher scores tended to decline at a greater rate in SBP (unstandardized ψSBP−I SBP−S = −0.26 [−0.43 −0.16], SE = 0.07, p < 0.001).

#### Hypothesis Two

In relation to wellbeing, a significant within-person decline in all components of SWB over the time period was found, thus supporting hypothesis two. A negative and significant mean latent trajectory was evident for LS (unstandardized TABLE 4 | Measurement and invariance testing.

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SBP, strength-based parenting knowledge. LS, life satisfaction. PA, positive affect. NA, negative affect. df, degrees of freedom. CFI, comparative fit index. TLI, Tucker Lewis index. M.I. EPC (stdyx), minimum expected parameter change, standardized. Model conventions: M, measurement. FL, full loading. FI, full intercept. PL, partial loading: freed loading survey item(s). PI, partial invariance: freed intercept survey item(s). t1-3 denotes survey wave. + a change in CFI of 0.01 or greater from the measurement model was adopted as the guideline for invariance acceptability. 1CFI, change in CFI from the measurement model to the present model. Maximum likelihood estimator was utilized for measurement and invariance testing. For PA, while partial loading invariance held, the decrement in fit was close to 0.01 (1CFI = −0.007), and as such loadings were freed before proceeding to tests of intercept invariance. Final model adopted and utilized in all LGM and RI-CLPM models for each factor is in bold.

µLS−S = −0.11 [−0.16 −0.06, SE = 0.03, p < 0.001), and PA (unstandardized µPA−S = −0.13 [−0.18 −0.08], SE = 0.03, p < 0.01), and a positive trend for NA (unstandardized µNA−S = 0.074 [0.03.22], SE = 0.03, p < 0.01). As with SBP, participants starting values influenced their change over time. Covariances between the intercept and slope factors in the LGM indicate participants who began with initially higher scores tended to decline at a greater rate in PA (unstandardized ψPA−IPA−S = −0.09 [−0.15 −0.04], SE = 0.03, p < 0.001) and increase more for NA (unstandardized ψNA−I NA−S = −0.05 [−0.11, −0.01], SE = 0.03, p < 0.01).

#### Hypothesis Three

The LGM also tested whether rates of change in SBP and aspects of SWB were related. A significant slope correlation between SBP and wellbeing variables was evident. Increases in SBP during the study period was associated with growth in LS (unstandardized BSBP−SLS−S = 0.05 [0.02,0.079], SE = 0.02, p < 0.001) and PA (unstandardized BSBP−SPA−S = 0.06 [0.03,0.09], SE = 0.02, p < 0.001); but not NA (standardized BSBP−SNA−S = 0.01 [−0.03,0.03], SE = 0.02, p < 0.430); partially confirming hypothesis three.

#### Hypothesis Four

Three RI-CLPMs each tested the potential causal and reciprocal relationships between SBP and LS, PA and NA. Non-positive definite matrices were encountered using the ML estimator, and, as such, a Bayesian estimator with 10,000 iterations was utilized with default diffuse uninformative priors, as in the LGM. The final measurement models adopted were per invariance testing. Results of the RI-CLPMs are presented in **Figures 1**–**3**.

As with the LGM testing, the RI-CLPMs found significant positive contemporaneous effects between SBP with LS, PA and NA at time 1 and then again between SBP with LS and PA at time three. These results, described by some as "correlated change" (Keijsers, 2016), are in line with the LGM and also with past findings of the beneficial effects of SBP on teen wellbeing and suggest that SBP is important factor for teenager wellbeing in their immediate time frames (Loton and Waters, 2017).

In relation to the test of time-variant stability/instability, the random intercept was significant in each model for each variable, although smaller in the case of NA: SBP-U (in the LS model) = 0.29 [0.01 – 2.4], SE = 0.64, p < 0.001; LS-U = 0.26 [0.01 – 1.13], SE = 0.32, p < 0.001; PA-U = 0.24 [0.03 −0.69], SE = 0.54, p < 0.001; NA-U = 0.06 [0.01 −0.53], SE = 0.14,

p < 0.001. The ICC for each between-variable (i.e., 'random intercept' latent trait variance/total average variance for each latent factor from times 1–3) indicate most variance was timespecific/within-person. The between-person proportions for SBP were 13.0%, LS = 24.7%, PA = 33.8%, and NA = 34.7%. In the present case, a participant's level of SBP at time one did predict SBP at time two (∼6 months) but this effect was not retained over the second lag (∼9 months). These results are consistent with past research showing that parenting is characterized by stability and change (Holden and Miller, 1999).

The substantive parameters of interest in the RI-CLPM are the cross-lagged paths, which represent an indication of causal predominance, and are interpreted as 'predicting change' at the within-person level (Hamaker et al., 2015, p. 104). In our models, all cross-lagged paths were not significant, pointing instead to possible 'third factors' that may explain the strong positive contemporaneous effects evident between SBP and SWB.

#### Power Analysis

With a sample of N = 202 and 82 parameters freely estimated in the RI-CLPMs, the sample size to parameter ratio exceeds common guidelines (Bentler and Chou, 1987). However, the indicators to latent factor ratio is relatively high, which is sometimes thought to compensate for the detrimental effect of small samples on power in SEM (Marsh et al., 1998). As such, a post hoc power analysis was undertaken using Monte Carlo simulation (see Muthén and Muthén, 2002) of the Bayesianderived estimates, to determine the increase in sample size required for CL effects to reach a significance level of p < 0.05. Results are presented in **Table 5**. Based on these simulation specifications, the CL path results held even in simulated samples up to N = 5002.

## DISCUSSION

Early adolescence is a pivotal period of development and parents play a key role in the mental health of young people during this life stage (Bruyn et al., 2003; Galambos et al., 2003; Bøe et al., 2014; Steinberg, 2014). Understanding the role of positive parenting on teen SWB motivated the present study. With past evidence for the concurrent and two-wave repeated measures beneficial effects of SBP on teen wellbeing (Waters, 2015b; Loton and Waters, 2017; Waters et al., 2019), we extended the time frames to a three-wave, fourteen-month study. Based on findings in past studies in the field of parenting research, we hypothesized a decline in SWB (hypothesis one) and SBP (hypothesis two) together with a relationship and causal impact of SBP on SWB over time (hypotheses three and four respectively).

Three of the four hypotheses were supported. Firstly, as predicted, SWB diminished significantly over time, confirming hypothesis one. Specifically, LS and PA declined while NA increased over time. Secondly, within-person SBP significantly declined over the study period, supporting hypothesis two. Thirdly, teens who reported a decrease in SBP over the study period also tended to experience declines in LS and PA, but no

SBP, strength-based parenting knowledge. LS, life satisfaction. PA, positive affect. NA, negative affect. Initial sample N = 202, repetitions = 500, seed = 45355, population and coverage both defined by the Bayesian RI-CLPM outputs.

change to the trajectory of NA, as revealed through the LGM analysis. The same beneficial contemporaneous effects of SBP on LS and PA, but not NA, were evident in correlated change at T1 and T3 through the RI-CLPM analyses, thus providing partial support hypothesis three. In regards to hypothesis four, we examined these dynamic relationships by applying a causal panel modeling framework that partitions variance into stable/timeinvariant components and links within-person fluctuations across each wave for each variable (Hamaker et al., 2015). In these models, results were partially supportive of the SBP-SWB link but did not support direct causal effects. The cross-lagged paths indicated that within-person changes in SBP did not predict increases in SWB over time, or vice-versa, thus failing to support hypothesis four.

When the causal analysis framework was applied, the degree of stability across factors ranged from 13% to 34.7% of variance apportioned to between-person stability which highlights the importance of modeling change in a multi-level framework. In addition, rank-order stability in SBP held only in the first 6 but not over the ensuing 9 months, showing a pattern of variance-invariance in parenting, and supporting past research that positive parenting changes through the adolescent years.

The decline in wellbeing during early adolescence is highly consistent with past research (Ullman and Tatar, 2001; Suldo and Huebner, 2004; Park, 2005) and is likely to be a function of the significant life changes young people go through when stepping into the second decade of their lives. Developmental psychologists have long identified that the shift from childhood into adolescence marks a time of intense social, physical, identity and economic changes (Larson and Wilson, 2004; Sodha, 2009; Dorn and Biro, 2011). Together with increases in responsibilities and academic pressures, these changes put early adolescents at risk of mental ill-health (Frigerio et al., 2009; Anselmi et al., 2010).

Neuroscientists have also now added to our understanding of why mental health declines in this age bracket by showing that adolescence is a time where the brain is particularly vulnerable to stress and depression (Andersen and Teicher, 2008) because it is undergoing rapid change (Giedd, 2008), including the process of synaptic pruning of gray matter coupled with new production of white matter (Giedd, 2008). The 'back to front' development of brain structures in the teen years from the amygdala, through to the hippocampus and on to the prefrontal cortex lead to the situation where the emotional systems of the brain develop faster than the cognitive systems of the brain (Sowell et al., 2001) which has been posited as a reason for greater emotional sensitivity and vulnerability in the teen years. Ernst et al. (2006) hypothesized that adolescent depression may emerge because the limbic structures that drive negative emotions mature more quickly than the pre frontal cortext which assists teens to regulate their mood. Toward the end of adolescence and in early adulthood the brain becomes more integrated and connected (Paus et al., 2008), and the cognitive systems catch up with emotional systems which scientists suggest is a reason why the risk for psychopathology diminishes in early adulthood (Giedd, 2008).

Importantly, neuroscientists have also shown that the type of parenting that occurs in the life of a young person transitioning into early adolescence has a significant impact on mental health. For example, early teens whose parents had displayed contemptuous, angry, impatient, belligerent, disapproving, threatening, or argumentative behaviors during a lab experiment in their late childhood were more likely to experience the onset of depressive symptoms and major depression in adolescents (Yap et al., 2008; Schwartz et al., 2011). Conversely, early teens whose parents related to them in approving, validating, affectionate, humorous, happy, pleasant, and/or caring ways, showed beneficial brain growth in regions that supports a teenager's capacity for social-emotional functioning as well as declines in areas that make an early adolescent vulnerable to mental illness9 (Whittle et al., 2014).

9 In this neuroscientific study, positive maternal behavior was linked to accelerated cortical thinning in left and right orbitofrontal cortices, between baseline and follow up. Thinning of the orbitofrontal cortices is associated with superior cognitive functioning. For boys there was also a thinning in the right anterior cingulate. Thinning of the orbitofrontal cortices is associated with superior cognitive functioning. Thinning of the orbitofrontal cortices and anterior cingulate

In line with the above research that highlights the importance of positive parenting for youth wellbeing, both the LGM and RI-CLPM analyses revealed a pattern of positive contemporaneous effects between SBP and SWB. When pre-teens and early teens are asked to reflect on the parenting they receive and, at the same time, report on their wellbeing, a significant relationship is present. These results are consistent with those found across multiple samples of teens where SBP has been related to a range of wellbeing indicators such as SWB (Jach et al., 2017), life satisfaction (Waters, 2015b), happiness and self-efficacy (Loton and Waters, 2017), subjective happiness (Sagkal and Özdemir, ˘ 2019), and family happiness (Waters, in press).

Waters has argued that having strength-based parents provides teens with an interpersonal context that supports the development and reinforcement of strengths (Waters, 2015b). In support of this, Jach et al. (2017) found that SBP increased teen's use of their strengths. Other studies have shown that strengths-use and development is a significant factor in youth well-being (Proctor et al., 2011; Suldo et al., 2014). Adding to the interpersonal context triggered by SBP, Waters (2015a) proposed that SBP creates an intrapersonal trigger for positive self-identity because having knowledge of one's strengths creates a lens through which teens engage with the world and, thus, a positive filter for teen identity. Related to this, past research has shown that SBP predicts positive aspects of teen identity such as self-efficacy (Loton and Waters, 2017) and mental toughness (Sagkal and Özdemir, 2019 ˘ ).

An important finding in the current study was the nonsignificant relationship between SBP and SWB over time. While the degree of SBP teens reported that they were receiving was linked to their levels of LS and PA in 'real time'10 this real time relationship did not transfer to longer time frames. That is, SBP at time one was not predictive of SWB at time two or three (6 and 14 months later). Likewise, SBP at time two was not predictive of SWB at time three (9 months later). This finding differs to past studies that have found SBP significantly predicts life satisfaction 12 months later (Waters, 2015b) and academic performance 3 months later (Waters et al., 2019). However, these past studies did not employ the stringent statistical analysis of RI-CLPM.

One reasons why SBP may not predict future SWB for early adolescents could be the reduction in the parent–child closeness that occurs during this particular life stage. Certainly, it is well recognized that increased distance and separation between parent and child are characteristic of the age bracket targeted for the current study due to the psychological need for 'individuation' (Levy-Warren, 1999). Larson and Richards' (1991) study of differences in time spent with parents between 5th and 9th graders found that early teens spent 40% less time with their parents than those in their late childhood. This life stage also marks a period of emotional distance and research shows that reductions in parent-child closeness together with increases in child secrecy are especially prominent in the early adolescent years (Larson and Richards', 1991; Keijsers et al., 2010). Steinberg and Silverberg (1986) assert that young teens no longer allow their parents to know everything about their lives. The process of separation and distance that unfolds during early adolescence may explain why parenting approaches that are present in the beginning of this study (e.g., pre-teens) are not having an impact on the wellbeing of the young person 14 months later because the relationship is become more distant. Future researchers could include measures of teen-parents closeness and conflict to test for the potential mediating or moderating effects of these two variables on changes to teen ratings of SBP over time. It might also be fruitful for future researcher to collect data about SBP from teen-parent dyads or triads (see Waters, 2015b) to examine the way parent-teen perceptions of SBP interact and change over time. The degree to which parent-teen perceptions of SBP get more aligned or more discrepant over time might influences psychological outcomes such as subjective wellbeing.

Whatever the cause, the results of this study indicate that parents cannot assume that their prior, or current, levels of SBP are 'banked' by their children to support future wellbeing. Instead, SBP needs to be a frequent, ongoing approach. Indeed, the fact that SBP was related to LS and PA in real time in our sample suggests that parents can contribute to the wellbeing of their sons and daughters at each step along the way by committing to regularly helping their pre-teens and teens cultivate their strengths.

Despite the importance of SBP, it was not consistent over time in current study with the youth samples' ratings of SBP declining. The current findings are similar to past research showing a decline in a range of positive aspects of parenting such as parental warmth, support, involvement, and regard (McGue et al., 2005; Hafen and Laursen, 2009). Therefore, the decline in SBP that we observed may be related to this particular life stage, and the changes in the parent–child relationship that occur during this time. Waters (2015b) argues that SBP provides interpersonal benefits but it may be that in the early adolescent phase, a phase marked by increased parent-teen conflict, being strength-based is more difficult to achieve. The negative emotions that arise through conflict may heighten certain cognitive biases, such as the negativity bias in either the parent or the teen (Baumeister et al., 2001; Robin and Foster, 2002), making them focus more on problems and challenges rather than strengths and opportunities.

The reduction in SBP may also be to do with intrapersonal changes that occur for teens during this stage, especially the identity changes and increases in self-doubt. Klimstra et al. (2010) found that identity uncertainty increased in early to-middle adolescence. Increased self-doubt in the teen may mean that, even if the parent remains constant in their strength-based approach, the teen is not able to consistently absorb and integrate the positive feedback, thus accounting for reports of declines in SBP.

#### Study Limitations and Future Research

This study has a number of positive features. It provides an example of a thorough analysis of observational panel data examining the relationship between parenting and wellbeing

cortices is associated with higher temperamental effortful control (i.e., selfregulation and impulse control) and lower levels of internalizing behaviors (e.g., depression and anxiety). This research also found reduced growth of the right amygdala. Reduced growth in the amygdala is associated with a lower fear response, lower emotional reactivity and higher emotional regulation abilities. 10The significant relationship was found at the baseline and 14 month re-tests.

in an important life phase - early adolescence. The rigorous statistical modeling using both LGM and RI-CLPM are a strength of this study and encourage future researchers to ensure that the nuanced changes in phenomena over time are adequately tested. The measures were psychometrically sound and had been used in prior research. The sample was drawn from a socio-economically typical school rather than a focus on at-risk students allowing us to examine an under-explored strata of families. The study took an asset-based approach and adds to the small, but growing, literature on positive parenting, thus responding to the criticism of the parenting literature being overly deficit-oriented.

Alongside the above assets of the paper, we must also recognize several weaknesses. Firstly, the study was only able to provide a view of how SBP and SWB changed over 14 months. Given that early adolescence stretches over 3 years the study may have found different results had we extended the time lines. Perhaps SBP may have been causally linked with SWB had we followed the sample for longer into the next stage of adolescence where parents and their teens become closer again.

Secondly, the time points of data collection within the 14 month timeframe may have been too long to meaningfully examine causality. Six months and nine months are a long time in the life of a teen whose minds track time differently to adults (Steinberg, 2008). The current study suggested that temporal dynamics between SBP and SWB could instead operate in short timeframes, and future research may choose to use methods that tap more into the 'real time' dynamics such as daily diary methods (Fisher and Gershuny, 2013) or experiential sampling methods (Hektner et al., 2006) in order to better explore the mechanisms that are underpinning the SBP-SWB link.

Thirdly, the small sample size relative to the large number of estimated factors is another limitation, although a Monte-Carlo analysis simulating larger samples sizes with identical parameter solutions supported no change on that basis to the results. The use of Bayesian rather than ML estimators in the present study, increasingly used in dynamic examinations (Asparouhov et al., 2018), provides an example for social scientists wanting to model complex factors in small samples over time. Future similarly designed studies with larger samples are required to confirm the present results.

#### REFERENCES

#### CONCLUSION

Seligman and Csikszentmihalyi (2000) assert that "promoting competence in children is more than fixing what is wrong with them. It is about identifying and nurturing their strongest qualities, what they own and are best at, and helping them find niches in which they can best live out these strengths" (p. 6). The current study is relevant for professionals working with parents and prompts them to encourage parents to maintain a strength-based approach over time, so as to avoid the more typical patterns of parent-child decline in early adolescence. The study offers several opportunities for future research on this topic and we hope to be part of an ever-growing movement toward the study and practice of positive parenting.

#### ETHICS STATEMENT

This study was approved by The University of Melbourne Human Research Ethics Committee, application number 1748708.

#### AUTHOR CONTRIBUTIONS

LW drafted and substantially edited the literature and discussion. DL and MZ undertook the analysis and wrote the "Materials and Methods" and "Results" section. DL assisted in drafting the introduction and substantially drafted the first draft of the discussion. DG reviewed the literature and drafted most of the first draft of the introduction. RJ-H assisted with critical feedback and data preparation.

#### FUNDING

The work of DG and RJ-H were supported by a Gerry Higgins Studentship, a Scholarship program within the Centre for Positive Psychology at The University of Melbourne.

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onset of major depression. Behav. Res. Ther. 49, 331–338. doi: 10.1016/j.brat. 2011.02.008

Schwartz, O. S., Sheeber, L. B., Dudgeon, P., and Allen, N. B. (2012). Emotion socialization within the family environment and adolescent depression. Clin. Psychol. Rev. 32, 447–453. doi: 10.1016/j.cpr.2012.05.002

Seligman, M. E. P. (1999). The APA 1998 annual report. Am. Psychol. 8, 539–567.

involvement, and encouragement to succeed. Child Dev. 63, 1266–1281. doi: 10.1111/j.1467-8624.1992.tb01694.x

**Conflict of Interest:** LW has published a book on strength-based parenting and has been a speaker, including as an invited keynote, both pro bono and remunerated, at a number of conferences speaking on the topic of strength-based parenting. LW is co-founder of The Strengths Exchange, a website offering free strength-based resources and tools to parents (http://www.the-strengths-exchange. com.au).

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Waters, Loton, Grace, Jacques-Hamilton and Zyphur. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Father Involvement and Cognitive Development in Early and Middle Childhood: A Systematic Review

Luca Rollè, Giulia Gullotta\*, Tommaso Trombetta, Lorenzo Curti, Eva Gerino, Piera Brustia and Angela M. Caldarera

Department of Psychology, University of Torino, Turin, Italy

This systematic review aims to examine the existing literature concerning the association between father involvement and the development children's cognitive skills during early and middle childhood. Specifically, it analyzes: (1) how the number of researches developed across years; (2) which are the main socio-demographic characteristics of the samples; (3) which are the main focuses examined; and (4) which operational definitions were used to assess father involvement and children cognitive skills. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, the articles were searched through PubMed and EBSCO (PsycInfo, PsycArticles, Education Source, Social Sciences Abstract, Family Studies Abstracts, Gender Studies Database and CINAHL complete). The findings suggest that, although each research used a different operational definition of the father involvement construct, in recent years there was a wide and constant interest increase about this issue. Most of the empirical studies utilized quantitative methods, whereas relatively few used qualitative and only one mixed methods. As regards the analysis of socio-demographic characteristics of the samples there is a great evidence that most of them included biological and residential fathers: it may reflect that this type of sample is easier to recruit than non-residential and non-biological fathers. Regarding the socio-economic status and the ethnicity of families, the data highlighted how in recent years the literature on father involvement is starting to look at differences in ethnic and cultural backgrounds, in contrast to past researches. The findings revealed that the main focus is the impact of father involvement on children's cognitive skills and the most of the studies highlighted that it is positive and statistically significant. Regarding to the assessment of father involvement and children's cognitive skills, the literature is quite heterogeneous

Keywords: fathers, fathers involvement, cognitive skills, learning, parenting

#### INTRODUCTION

Cognitive skills development is a broad concept that involves the maturing of a variety of abilities and is defined by the American Psychological Association (VandenBos, 2015) as "the skills involved in performing the tasks associated with perception, learning, memory, understanding, awareness, reasoning, judgment, intuition, and language" (p. 202). In this process, as Bandura highlighted in 1993, parents can play a crucial role, contributing to stimulating and supporting children's self-regulatory and cognitive development (Bandura, 1993). Indeed, parents who undertake verbal interactions

*Edited by:*

Yvette Renee Harris, Miami University, United States

#### *Reviewed by:*

Nicola Carone, University of Pavia, Italy E. Helin Yaban, Hacettepe University, Turkey

*\*Correspondence:* Giulia Gullotta<EMAIL_ADDRESS>
#### *Specialty section:*

This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology

*Received:* 09 April 2019 *Accepted:* 09 October 2019 *Published:* 25 October 2019

#### *Citation:*

Rollè L, Gullotta G, Trombetta T, Curti L, Gerino E, Brustia P and Caldarera AM (2019) Father Involvement and Cognitive Development in Early and Middle Childhood: A Systematic Review. Front. Psychol. 10:2405. doi: 10.3389/fpsyg.2019.02405

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and structure activities and games with their children allow them to live the rich linguistic communication and contexts of shared attention and meanings. These experiences encourage children's active exploration and engagement with their environments, improving children's academic skill and their success in school (Grossmann et al., 2002). Paternal involvement has been also situated within Bronfenbrenner's bioecological theory (1979) which highlighted that both proximal (e.g., paternal involvement) and distal (e.g., socioeconomic status, race/ethnicity, school context) factors must be considered to fully understand paternal influences on children's cognitive skills development. In line with these findings, various meta-analyses and reviews investigated the link between parental involvement during early and middle childhood and student achievement (e.g., Fan and Chen, 2001; Jeynes, 2007) and proximal and distal factors influence levels of fathers' involvement in literacy activities (e.g., Varghese and Wachen's, 2016). Even though various proximal and distal factors (e.g., fathers' education, income level, residencial status, relationship with the child's mother) are indirectly associated with children's language development and literacy activities (Varghese and Wachen, 2016), research confirmed a direct, positive and relatively strong association between paternal involvement and children's cognitive skills development (Fan and Chen, 2001; Jeynes, 2007). For instance, Varghese and Wachen (2016) found that fathers made unique and direct contributions to their children's literacy outcomes through their engagement in reading and writing activities and the use of complex language and responsive parenting behaviors.

However, notwithstanding the extensive literature on the topic, there is a great difficulty in finding an agreed definition of the construct of parental involvement, as it is conceptualized in a variety of ways (Harris and Goodall, 2007). For example, some authors distinguish between school- and home-based involvement: the first refers to the communications between parents and school personnel and to the parental engagement in activities children must perform at school (Grolnick and Slowiaczek, 1994; e.g., Hill, 2001), while the second (homebased) includes all the school activities that both mothers and fathers perform with their children at home (Hill, 2001). Other researchers investigated a further form of parental involvement not directly related to school (e.g., playing sports and other games, going to the cinema or a museum) that can influence school achievement (Nord et al., 1997).

Furthermore, while the first studies on the influence of parenting on children's outcomes focused mostly on mother– child dyadic interaction, nowadays, given the increasing number of working mothers and the changing social climate regarding male and female gender roles, the assumption that mothers were the gatekeepers and that father–child relationships had little impact on children's development is diminished. Consequently, various current studies are focused on the construct of coparenting as "the ways that parents work together in their roles as parents" (Feinberg, 2003, p. 1499) and to explore the determinants of fathers' involvement with their children's education (Lamb et al., 1985; Volling and Belsky, 1991). One of the most widespread and accredited models of the construct of father involvement was developed by Lamb et al. (1985). It includes: (a) engagement, the amount of time fathers spends in direct contact with their children (e.g., verbal stimulation, caregiving, and physical play); (b) accessibility, fathers' attendance and availability; and (c) responsibility, the ability to plan activities specifically adapted to the age and needs of the child (Lamb et al., 1987). Although this model allowed an increase in the understanding of the ways in which fathers are involved in their children's lives, it showed various gaps (Fagan et al., 2014). First, given the lack of systematic development regarding the different heuristic categories, there are only a few validated and reliable tools. Second, of the three types of involvement suggested by Lamb et al. (1985), researches have generally focused more on paternal engagement than on accessibility and responsibility, resulting in an overfocus on the amount of time fathers spend with their children (Pleck, 2012). As a consequence, Pleck (2010) widens the definition of "engagement," identifying two distinctive elements: (a) positive engagement activities, the amount of time fathers and children are involved in interactive activities, such as reading books and teaching, that may promote learning and development; and (b) the dimensions of parenting, how fathers engage with their children, including the dimensions of Baumrind's (1967) parenting style model (responsiveness and demandingness). This contribution showed that the originally engagement construct may be not well-defined for studying the effects of fathers' parenting on children. However, many gaps related to the original tripartite model remained (Fagan et al., 2014). One of these gaps is that positive engagement was still largely focused on the amount of time fathers are involved with their children; another is related to the lack of a valid theory that guided the selection of the different dimensions of positive father engagement. In addition, the multidimensional construct has not been integrated into a comprehensive conceptual framework that could enable an understanding of what fathering is, why fathers parent in the manner they do, and how paternal actions directly and indirectly help determine children's development (Palkovitz, 2002; Pleck, 2007, 2010). To overcome this research gap, Cabrera and Volling (2019) proposed a "Developmental Ecological Systems Framework for understanding fathering and children's development." This approach considers fathers as part of dynamic systems characterized by interconnected relationships between and among caregivers and children and explains how these relationships evolve and change through time and social and contextual factors (Cabrera et al., 2014, 2018). Previously, based on this ecological approach, Cabrera et al. (2014) developed a model to acknowledge the flow and actions affecting the quality (and quantity) of fathering on child functioning. According to this model, the father–child relationship results are influenced by the personality, personal characteristics, and behaviors of the father and other family members (e.g., mother, child, siblings) and the overall context of the family system by the family relationship (e.g., coparenting), the different family households, socioeconomic statuses (SES), and cultures, and the child's and family's development (Volling and Belsky, 1991; Cabrera et al., 2014; Cabrera and Volling, 2019). The strengths of this model are the inclusion of interpersonal and contextual variables in determining the level of father involvement (Volling and Belsky, 1991) and, also, the consideration of the transactional and reciprocal relationships between fathers and children (Sameroff, 2010). In line with complexity put in light by this model, the literature about father involvement is still very heterogeneous. As a consequence, in order to design innovative and rigorous research, it becomes necessary to increase knowledge about what has been previously investigated, particularly in relation to the following issues: how should father involvement, especially in early and middle childhood, be conceptualized and measured? What is the relationship between the different components of father involvement and children's cognitive skills? Which are the main focuses investigated? Are non-residential, step-, low-income, and minority fathers included in the research samples? How is it possible to increase father involvement in children's education?

Although some attempts of synthesis have already been produced, many are prior to 2010 (Saracho, 2007a,b; Downer et al., 2008), while the more recent are focused on specific themes, such as educational achievement (Lipscomb, 2011; Jeynes, 2015; Kim and Hill, 2015), and none were published after 2016. Consequently, the previously presented questions call for a systematic examination of the existing research concerning the association between father involvement and children's cognitive skills during early and middle childhood, to widen our knowledge about the definition and measurement of father involvement, the pathways of its influence on children's cognitive skills development, and the differences from/similarities to mother involvement.

#### AIMS

The aims of the present review are to systematically examine the literature about father involvement in the development of children's cognitive skills and, in particular, to analyze: (1) how the number of researches and the design/methods developed across years; (2) if non-residential, step-, low-income, and minority fathers are included in the research samples; (3) which are the main focuses of the examined literature; (4) which operational definitions of the construct and measures were used to assess father involvement and children's cognitive skills.

#### METHODS

#### Data Source and Search Strategy

We followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Moher et al., 2009). Articles were searched through PubMed and EBSCO (PsycInfo, PsycArticles, Education Source, Social Sciences Abstract, Family Studies Abstracts, Gender Studies Database, and CINAHL Complete).

We examined titles and abstracts to find eligible studies published in English, from the first publication in 1964 to November 2018. The keywords used for the query were "Father∗ " and "learning" or "cognitive skills" and "children." Of the 2,215 papers resulting from this first search, after duplicates removal, 777 met the criteria of being published in English in peerreviewed journals. We selected, by titles and abstracts, 178 papers. As a second step, we selected the papers to be included in the data synthesis by reading the full-text. A total of 40 papers was finally retained (see **Figure 1**).

#### Study Inclusion and Exclusion Criteria

The inclusion criteria for the papers were: (a) the presence of the father involvement construct and a specific reference to cognitive skills; (b) age of children not above thirteen; (c) written in English; and (d) published in academic journals. Both qualitative and quantitative articles were selected as well as reviews, with the aim of looking at the different approaches and methodologies used in this field.

The exclusion criteria were: (a) clinical samples to avoid bias in focusing more on father involvement as related to the outcomes associated with disease (e.g., ADHD, autism); (b) studies that were not specifically focused on the father involvement construct; (c) adolescent samples (2 studies with 10-year-old children were excluded because they were part of samples aged between 10 and 16 years); and (d) studies focused on other children's outcomes (e.g., physical, diet). Two independent reviewers selected the articles by title and abstract. Afterwards, they compared the results to determine a common list of selected papers; each choice that was different between the two reviewers was discussed in order to find an agreement.

#### Strategy for Data Synthesis

The selected articles were independently entered by each reviewer into two classification tables: one dedicated to analyzing the reviews and meta-analyses, and the other to analyzing the qualitative, quantitative, and mixed-methods studies. The papers that, when reading the full text, did not match our selection criteria were further excluded. Each reviewer independently completed the tables, and discussed each discrepancy in the selection in order to find an agreement.

We subsequentely developed a dataset of the selected papers and conducted a thematic analysis (TA) with the purpose of defining the main focuses of the reviewed articles, using a semantic approach, according to the guidelines provided by Braun and Clarke (2006). The reviewers discussed the TA results as well.

To avoid a thematic overlap, each article was linked to a single topic, in particular, the main focus of each study.

#### RESULTS

**Table 1** shows the frequency of the different types of papers. Quantitative methods were mostly used, whereas there were few qualitative and only one utilized mixed methods.

**Table 2** (meta-analyses and reviews) and **Table 3** (empirical studies, case reports, and theoretical articles) describe the researches' primary characteristics—authors and year, study design, objective, content focus, determinants, and key findings in relation to general information and our review question. Other features of the reviewed literature will be discussed in detail in the following four paragraphs: growing interest with

the role of father involvement in children's education, and the samples' sociodemographic characteristics, main focuses, and measurement methods.

#### Growing Interest in the Role of Father Involvement in Children's Education

This paragraph's main objective is to expand on the state of the literature about father involvement in children's cognitive skills development. One of the more widespread problems was that, in the literature on caregiving and children, fathers' parenting has been studied less than mothers' (Downer et al., 2008).

However, in the 70s and 80s the scholarly interest in fatherhood grew (Lamb, 2004) and, during the 90s, there was an increase in the researches on various fatherhood aspects, developing a large and heterogeneous body of studies that emphasized the unique role of fathers in children's development. For example, Marsiglio et al. (2000), in their review about fatherhood, examined the relationships between the dimensions of the father–child relationship (e.g., time spent with children, emotional support, everyday encouragement, and overseeing children's behaviors) and children outcomes. The increasing trend of the number of articles specifically focused on the construct of "father involvement" in children's education is shown in **Figure 2**. In the next paragraphs, we will focus on the main sociodemographic characteristics and measurement methods used in this growing literature.

#### Samples' Demographic Characteristics

Regarding age, father involvement research was mostly conducted on groups of children aged 0–6 (27.5%), preschoolers

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(3–5) (22.5%), and infants/toddlers (0–3) (20%); mixed age (7.5%) and middle childhood samples (15%) were less frequent. However, reviews and meta-analyses focused on a wider age range, from early years to 20 years old.

Concerning fathers' characteristics, it is possible to see a predominance of biological and residential fathers: 35% of the reviewed studies collected samples of only biological fathers and more than 35% of only residential fathers. This trend may reflect that this sample type is easier to recruit. Indeed, only two studies used samples mostly comprised of non-residential fathers (Black et al., 1999; Baker, 2018). In the first quantitative study Baker (2018) investigated, in a sample of 74% non-resident fathers, father–school involvement was a predictor of improving academic achievement and social-emotional skills.

The results showed that, although mothers were always more engaged in their children's education, father–school involvement was positively associated with children's math and reading skills and with teacher-related approaches to learning during early childhood. In the second study with a sample composed of non-residential biological and non-biological African American fathers (who were involved at least monthly). Black et al. (1999) assessed the relationship between paternal roles (e.g., nurturance, emotional and economic support) and children's well-being.

The results showed that children whose fathers are satisfied with their parenting and economically supportive of their families have better language competences and cognitive skills, proving the unique fathers' contributions.

Nevertheless, regarding the families' SESs and ethnicities, we found a great heterogeneity across all the studies. Between the studies that distinguished minority, non-minority, and mixed ethnicity samples, 12.5% of the selected articles recruited only minority fathers, 30% exclusively focused on non-minority men, and 40% had a mixed ethnicity sample. More specifically, most of the studies that focused on minority or mixed ethnicity included African American (Black et al., 1999; Cabrera et al., 2011) and Hispanic fathers (Ortiz, 2000; Saracho, 2007a, 2008).

Despite the well-established relevance of household income for children's academic success, the research and knowledge about father involvement and children's cognitive skills in lowincome families were lacking. Among the reviewed articles that studied the SESs of the families with children in early and middle childhood, 20% centered on low-income fathers while 42% included a mixed sample with family income ranging from low to high.

#### Main Research Focuses

As shown in **Figure 3**, half the empirical studies and all the reviews and meta-analyses focused on the relationship between father involvement and children's outcomes; a good number also focused on the effectiveness of interventions to increase fathers' engagement with their children's education and on the comparison between mother and father involvement, while a few articles examined the determinants, and only one study addressed the issue of assessment. In the following subparagraphs, we will synthetize the literature for each research focus, except the assessment, which we will discuss in the next paragraph.

#### Extent of the Association Between Father Involvement and Children's Cognitive Skills

The findings of the reviewed articles (including reviews and meta-analyses), focusing in particular on the association between father involvement and children's cognitive skills, showed a positive and statistically significant association during early childhood (Flouri and Buchanan, 2004; McBride et al., 2005, 2009; Roopnarine et al., 2006; Saracho, 2007b; Downer et al., 2008; Coley et al., 2011; Fagan and Lee, 2012; McWayne et al., 2013; Duursma, 2014; Jeynes, 2015; Kim and Hill, 2015; Baker, 2017, 2018) beyond mothers' parenting (Roopnarine et al., 2006). More specifically, Fagan and Lee (2012) argued that this relationship was significantly strengthened for children living in single-mother households, whereas Coley et al. (2011) found that family characteristics were trifling.

However, it is important to underline that several studies highlighted that this pattern generally remains significant across ethnicity and SES (Downer et al., 2008; Jeynes, 2015; Baker, 2017).

For example, Cabrera et al. (2011) examined father engagement—verbal stimulation, caregiving, and physical play across race, monitoring marital status, parental conflict, parental education, and depressive symptoms. The findings showed that while Caucasian fathers demonstrate a lower involvement in care and physical play than African American and Latino fathers, there were no differences in verbal stimulation across ethnicity. Furthermore, fathers' education (i.e., college level) was linked with more verbal activities, whereas couple conflict was associated with less engagement in care and physical activities. In conclusion, the authors argued that, although the level of involvement differed across ethnicity, the general model did not change.

Conversely, some scholars found that the relationship between father involvement and children's cognitive skills diverges across children's and parents' gender (Tan and Goldberg, 2009; Eng et al., 2014), race, and SES (McBride et al., 2013).

For example, Baker et al. (2018) found that, although poverty negatively influences more fathers' than mothers' parenting, fathers' engagement was a stronger moderator between poverty and children's cognitive skills than mothers' involvement.

#### Comparison Between Maternal and Paternal Involvement

In addition to the studies that specifically focused on the relationship between father involvement and children's outcomes, another great part of research aimed at comparing TABLE 2 | Reviewes and meta-analysies included in the study.

maternal and paternal involvement in children's education. Most studies on this topic highlighted that, although the mean level of mothers' involvement was higher than fathers' (Duursma, 2014; Kim and Hill, 2015; Baker, 2018), fathers' involvement and children's academic skills had a positive association.

For example, Keown and Palmer (2014) collected a sample of 94 two-parent families, with the aim of comparing father and mother involvement with their young son. The findings revealed that, although the mothers were more available to their sons on workdays, and fathers were more involved in activities with their children on weekend days, both mother– and father– child conversations were rich resources for children during their school ages.

Another study, specifically focused on the comparison between maternal and paternal involvement, was conducted by Foster et al. (2016). The authors investigated the home learning environment (HLE) during early childhood and how mothers' and fathers' parenting practices predict children's academic outcomes. The findings showed that mothers provided HLE activities more frequently than fathers although, in families in which mothers had at most a high school diploma, fathers' contributions were a significant predicator of children's early academic skills. However, other studies indicate that also fathers' education levels were often associated with mother engagement and that parental education indirectly influences children's language development through multiple pathways (Pancsofar et al., 2010).

Furthermore, Duursma (2014) examined the association between book-reading frequency of low-income fathers and mothers and children's cognitive and literacy skills and found

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that, although mothers read to their children more frequently than fathers, approximately 55% of fathers reported that they read to their children weekly. Moreover, this study highlighted that fathers' book reading significantly predicted children's language competences, book knowledge, and cognitive skills.

In line with mentioned studies, Giallo et al. (2013) found quite a few differences between mothers' and fathers' involvement, despite both of them were influenced by parenatal self-efficacy (PSE), considering it one of the determinants of father involvement.

#### Determinants of Father Involvement

Another group of articles specifically focused on the determinants of father involvement, examining both contextual, and personal factors.

Ball (2009), in a qualitative study about the involvement of 80 Canadian Indigenous fathers, introduced a conceptual model that identified six key ecological and psychological factors of fathers' involvement in circles of care for children. The six found factors are: (a) individual health, (b) learning fathering (direct father–child interaction, role models, and direct instructions), (c) socioeconomic inclusion, (d) social support for positive involvement, (e) legislative and policy support for involvement, and (f) cultural continuity.

In the same direction, Bradley and Corwyn (2000) investigated the influence of factors related to context (e.g., income), child characteristics (e.g., temperament), marital quality, and mother's and father's occupation on paternal socioemotional investment toward their children. The results highlighted that paternal investment is a multidetermined construct: it was not possible to identify one single factor that played a predominant role.

In recent years, Nordhal et al. (2016) suggested a conceptual model based on the "social interaction learning model" (SIL; Patterson, 1982), regarding the protective and risk factors of father involvement. Given that the interactions between children and parents can be considered a two-way process (Patterson, 1982; Patterson and Fisher, 2002). Nordhal et al. (2016) distinguished protective factors for fathers, including mental functioning and contextual and personal resources, and protective factors for children, including typical development, male gender, and easy behavior. While the negative factors related to fathers were mental dysfunction and personal and contextual strains, and the negative factors for children were development difficulties, female gender, and difficult behaviors. According to the findings, given that protective and negative factors were positively associated to fathers' positive involvement and to negative reinforcement, respectively, these last two dimensions could be considered different parenting components.

Another study that focused on the determinants of father involvement in Cambodian American families showed that parents' social networks, academic ambitions, trust, gender attitudes, and fatalistic convictions can be considered predictors of parental involvement (Eng et al., 2014). As a consequence, the authors highlighted the need for educators who work with Cambodian American parents to consider mothers' and fathers' beliefs systems and to identify personal and contextual resources to increase parents' involvement in children's education.

To sum up, the examined studies make reference to the following factors as determinants of father involvement: fathers' and mothers' education, families' income level, residencial status, race-ethnicity, characteristics of fathers and children, motherfather relation and social support for positive involvement. Indeed, although the studies in this field are characterized by a great heterogeneity, there is a general agreement in the literature about the necessity to consider how personal (e.g., mental health, child temperament, personality), interpersonal (e.g., marital quality, coparenting), and contextual factors (e.g., social support, culture) influence one another on their impact on father involvement.

#### Programs to Increase Father Involvement

As seen, although many studies highlighted that mothers were engaged in their children's education more frequently than fathers (Duursma, 2014; Kim and Hill, 2015; Baker, 2018), at the same time, there is strong evidence that fathers can play a unique role in children's cognitive skills development (Flouri and Buchanan, 2004; McBride et al., 2005, 2009; Roopnarine et al., 2006; Saracho, 2007b; Downer et al., 2008; Fagan and Lee, 2012; McWayne et al., 2013; Duursma, 2014; Jeynes, 2015; Kim and Hill, 2015; Baker, 2017, 2018).

Consequently, in recent years, there was an increase in studies focused on the efficacy of father involvement interventions. Indeed, among the 40 selected articles, the focus most investigated, after the relationship between father involvement and children's outcomes, was the benefits and strategies that can improve father involvement in children's education.