parental socioeconomic status, communication, and children's vocabulary development: a...

Parental Socioeconomic Status, Communication, and Children’s VocabularyDevelopment: A Third-Generation Test of the Family Investment Model

Sara L. Sohr-PrestonSoutheastern Louisiana University

Laura V. ScaramellaUniversity of New Orleans

Monica J. MartinUniversity of California, Davis

Tricia K. NepplIowa State University

Lenna Ontai and Rand CongerUniversity of California, Davis

This third-generation, longitudinal study evaluated a family investment perspective on family socioeconomicstatus (SES), parental investments in children, and child development. The theoretical framework was testedfor first-generation parents (G1), their children (G2), and the children of the second generation (G3). G1 SESwas expected to predict clear and responsive parental communication. Parental investments were expected topredict educational attainment and parenting for G2 and vocabulary development for G3. For the 139 familiesin the study, data were collected when G2 were adolescents and early adults and their oldest biological child(G3) was 3–4 years of age. The results demonstrate the importance of SES and parental investments for thedevelopment of children and adolescents across multiple generations.

In contemporary American society, considerableemphasis is placed on individual efforts as meanstoward achievement. As a result, Americans aremore willing to acknowledge the role of internalcharacteristics in influencing achievement thanexternal factors like socioeconomic status (SES;Lareau, 2003). Despite this emphasis on individualresponsibility for achievement, social backgroundstill seems to play a role. For example, low SES hasbeen found to limit: (a) children’s readiness for kin-dergarten (Ramey & Ramey, 2004), (b) access toquality schools and supplies (Lareau, 2003), and (c)

postsecondary education and career chances (Dun-can, Yeung, Brooks-Gunn, & Smith, 1998; Sandefur,Meier, & Campbell, 2006).

The influence of SES discrepancies permeatesthroughout the life span, with individuals experi-encing effects before kindergarten entry and beyondtermination of schooling. SES’s power extends fur-ther once individuals reproduce and the next gener-ation experiences continued influence of earlier SES.One way in which parents’ SES may influence thenext generation is via early vocabulary develop-ment and subsequent educational attainment. Thatis, parents’ SES has been linked to children’s aca-demic achievement and cognitive and languagedevelopment (e.g., Roberts, Bornstein, Slater, & Bar-rett, 1999), but the process by which SES affectsthese outcomes is not yet understood, especiallyacross multiple generations.

Our goal was to evaluate mechanisms by whichtwo different markers of SES, parent education andfamily income, influence vocabulary and educa-tional development for children and adolescents. A

This research is currently supported by grants from the EuniceKennedy Shriver National Institute of Child Health and HumanDevelopment, the National Institute of Mental Health, andthe American Recovery and Reinvestment Act (HD064687,HD051746, MH051361, and HD047573). The content is solely theresponsibility of the authors and does not necessarily representthe official views of the funding agencies. Support for earlieryears of the study also came from multiple sources, includingthe National Institute of Mental Health (MH00567, MH19734,MH43270, MH59355, MH62989, and MH48165), the NationalInstitute on Drug Abuse (DA05347), the National Institute ofChild Health and Human Development (HD027724), the Bureauof Maternal and Child Health (MCJ-109572), and the MacArthurFoundation Research Network on Successful Adolescent Devel-opment Among Youth in High-Risk Settings.

Correspondence concerning this article should be addressed toSara L. Sohr-Preston, Department of Psychology, SoutheasternLouisiana University, Hammond, LA 70402. Electronic mail maybe sent to [email protected].

© 2012 The AuthorsChild Development © 2012 Society for Research in Child Development, Inc.All rights reserved. 0009-3920/2013/8403-0021DOI: 10.1111/cdev.12023

Child Development, May/June 2013, Volume 84, Number 3, Pages 1046–1062

unique aspect of this study is that SES-relatedparental investments in children were examinedacross three familial generations. That is, we con-sider the relations among first-generation (G1) SESand parental investments during the second genera-tion’s (G2’s) adolescence and G2 educational attain-ment during early adulthood. We then examine thesame investment process regarding the children(G3) of these young adults, resulting in an intergen-erational examination of the potentially far-reachinginfluence of SES.

Family income and parental education are widelyaccepted indicators of SES representing differenttypes of capital. Income measures financial capitaland education measures human capital (e.g., Conger& Dogan, 2007; Conger & Donnellan, 2007; Hoff,Laursen, & Tardif, 2002; Oakes & Rossi, 2003).Theoretically, human capital affects children’sdevelopment by shaping parents’ goals for offspringsuch that their own human capital promotes humancapital in the next generation (Conger & Donnellan,2007). For instance, parents’ education may directlyshape expectations for children’s educational attain-ment as well as investments in children’s learning.More highly educated parents may spend more timecommunicating with their children and assistingtheir children with learning efforts (Conger &Dogan, 2007; Guo & Harris, 2000). In contrast tohuman capital that requires the investment of par-ents’ time, financial capital provides parents withopportunities to invest in goods, products, and ser-vices that enhance learning (Yeung, Linver, &Brooks-Gunn, 2002). Thus, benefits of parental edu-cation and income may have lasting impacts on thedevelopment and achievements of children.

These arguments derive from what Conger andcolleagues (Conger & Dogan, 2007; Conger &Donnellan, 2007) have called the family investmentmodel. This perspective originated in the economicsliterature (e.g., see Mayer, 1997) and Conger andcolleagues as well as others (e.g., Guo & Harris,2000; Yeung et al., 2002) have extended the modelfrom one solely concerned with income to oneencompassing more general aspects of SES (i.e.,income and parental education). The model pro-poses parents with higher income and more educa-tional attainment will make greater interpersonaland material investments in children’s developmentthan lower SES parents forced to focus on immedi-ate needs (Conger & Donnellan, 2007; Schofieldet al., 2011). Such investments will likely lead tomore positive developmental outcomes.

Some suggest associations among SES, familyinteraction processes, and child development may

vary by gender (see McLoyd, 1998, for a review), butstudies addressing such differences often supportmore similarity than differences in parents’ socializa-tion of boys versus girls (see Lytton & Romney,1991). Still, as differences have been supported inparents’ teaching with boys versus girls (e.g., Crow-ley, Callanan, Tenenbaum, & Allen, 2001) and inchildren’s behaviors toward fathers versus mothers(e.g., Leaper & Gleason, 1996), we examined the pre-dictions in the family investment model separatelyfor males and females when possible.

Evaluating the Family Investment Model AcrossGenerations

The proposed third-generation model (Figure 1)guiding this study begins with the direct relationbetween G1 SES (i.e., income and education) andG2 educational attainment (see Figure 1, Path b). Acentral proposition is that family SES will lead togreater human capital formation for children asthey grow to adulthood (Mayer, 1997). Consistentwith this hypothesis, research has shown that chil-dren from higher compared to lower income fami-lies tend to complete more years of education (e.g.,Considine & Zappalà, 2002; Duncan et al., 1998;Linver, Brooks-Gunn, & Kohen, 2002; Sobolewski &Amato, 2005; Turner & Johnson, 2003) and childrenwith better educated parents experience greatereducational success (e.g., Sandefur et al., 2006).

The family investment model also proposes thatassociation between parental SES and child devel-opment is explained, in part, by both material andinterpersonal investments parents make in children.The model in Figure 1 focuses on investments inthe form of clear and responsive communicationbetween parent and child. Previous evaluations of

G1 SES - Education - Income

G3 Receptive

Vocabulary

G2 Parental

Education

G1 Parental Communication

G2 Parental Communication

Family of Origin: G2 as Adolescents

Family of Procreation: G2 as Parents

a

d

c

g

e

b

f

Figure 1. A third-generation family investment model.

SES, Communication, and Vocabulary Development 1047

the investment model have focused on emotional(e.g., parenting beliefs, parenting behaviors, moni-toring, child-rearing enjoyment) and materialinvestments (e.g., reading materials, learning mate-rials, neighborhood, health insurance, quality of res-idence) in the G2 on G3 adaptive outcomes(Schofield et al., 2011), but none have consideredintergenerational continuities in parental communi-cation or its impact on learning outcomes duringlate adolescence (G2) or vocabulary developmentduring early childhood (G3). Admittedly, parentalcommunication probably covaries with otherparenting aspects, and is one specific element ofinvestments in children with evident relevanceto vocabulary development and educationalachievement.

Multiple factors underlie proposed differences inparental communication among higher versuslower SES families. Possibly, having more incomereduces stress from financial worries and leavesparents with more time and cognitive resourcesavailable for richer, clearer verbal communication.Alternatively, more general lifestyle differences mayshape parents’ values and schemas of how to speakwith children, meaning higher SES parents spendmore time speaking patiently and extensively withchildren and adolescents out of belief that theyshould do so rather than ability to do so. Indeed,both ideas have been tested, but it appears thatSES-related differences in parental communicationreflect general differences in verbal communicationwith all others, not just children (Hoff, 2003a).These overall communication differences includethat higher SES mothers tend to generally speakmore, speak longer, and use more diverse vocabu-lary (Hoff, 2003a), thus increasing the likelihoodthat offspring are exposed to a variety of wordsused in a rich assortment of ways. When parentsdeliver this rich verbal communication responsivelyand flexibly, with expectation and encouragementfor reciprocation, they go beyond merely offeringword exposure by affording verbal practice oppor-tunities to their offspring.

Consistent with the investment model, we expectG1 SES will influence G2 educational attainmentboth positively and indirectly via the degree ofclear and responsive parental communication dur-ing G2’s adolescence (paths a and c). This proposedmediated pathway represents the core explanatoryhypothesis of the family investment model,that higher SES parents invest more resources inefforts to promote children’s learning (Conger &Donnellan, 2007; Linver et al., 2002; Mayer, 1997).Although previous research demonstrates interper-

sonal investments enhance cognitive or academicoutcomes for children with either income (e.g.,Linver et al., 2002) or education used to measureSES (e.g., Hoff, 2003b; see Conger & Donnellan,2007, for a review), and although recommendationsto parents seeking to foster kindergarten readinesshave included engaging in rich and responsivecommunication (Ramey & Ramey, 2004), few stud-ies have considered these dynamics in adolescents’lives. Consistent with the model, research indicatesthat more parent–adolescent conflict is associatedwith declines in academic achievement during ado-lescence (Dotterer, Hoffman, Crouter, & McHale,2008), whereas data from our own study have indi-cated more positive parent communication duringadolescence promotes greater academic achieve-ment (e.g., Melby & Conger, 1996).

Noteworthy, however, is that we only predict G2educational attainment as a marker of later SESbecause the G2 target participants were assessedrelatively early during their adult years, at an aver-age age of about 23 years. Income at this time isnot a good indicator of SES inasmuch as manyof the participants who will attain the highest SES(i.e., those who eventually will have the highestincomes and years of education) may have rela-tively low incomes at this age. Indeed, education isconsidered by many to be the canonical element ofSES because of its influence on later income andoccupational status (Krieger, Williams, & Moss,1997). For these reasons, we chose education as themeasure of SES for G2 participants.

In a process similar to the dynamic proposed forlinks between G1 and G2, G2 educational attain-ment is expected to shape G3’s vocabulary develop-ment. Although the reasoning here is the same,more evidence supports this hypothesis duringchildhood than during adolescence. That is, bettereducated parents have been found to have youngchildren with more advanced language develop-ment (Burchinal, Peisner-Feinberg, Pianta, &Howes, 2002; Gest, Freeman, Domitrovich, &Welsh, 2004; Hoff & Tian, 2005; Raviv, Kessenich,& Morrison, 2004; Turner & Johnson, 2003) andhigher overall IQ (Linver et al., 2002). Interestingly,more educated mothers seem to expect their chil-dren to say first sounds and words and to “think”sooner (Hoff et al., 2002). Expecting more advancedchild vocabulary will likely increase parents effortsto encourage younger children’s learning experi-ences via clear and responsive communication (seealso Lareau, 2003).

We selected vocabulary as the G3 outcomebecause of its critical importance to development

1048 Sohr-Preston et al.

across childhood, adolescence, and adulthood(Schoon, Parsons, Rush, & Law, 2010). Of particularrelevance, children’s ability to understand a varietyof words is an essential component of kindergartenreadiness (Bierman et al., 2008; Doherty, 1997;Whitehurst & Lonigan, 1998). For instance, success-ful entry into kindergarten requires basic skills;many depend on vocabulary, including abilities tounderstand explanations and follow instructions.Children with limited vocabularies should experi-ence more difficulty during classroom activities.Such early academic problems, rather than fadingwith time, may place students on a persistent trajec-tory of academic problems (Shonkoff & Philips,2000), including repeating a grade, requiring specialeducation services, or leaving high school withoutobtaining a diploma (Brooks-Gunn, Guo, & Fursten-berg, 1993; Ramey & Ramey, 2004).

Moreover, young children with more advancedvocabulary do better in school over time and dem-onstrate greater academic achievement (Jorgenson& Jorgenson, 1996). Consequently, preschool-agedG3 children with larger vocabularies will likelyeventually achieve more academically on averageand thus have access to more diverse higher educa-tional and career opportunities. Similarly, it is likelythat the G2 young adults who achieved the mostacademically typically had above average vocabu-lary skills as young children.

Another step involves the direct path (d) from G1to G2 parental communication. While parental com-munication style has important implications for chil-dren’s vocabulary development, little is knownregarding the mechanisms by which parents learnto communicate with children. Possibly, parentslearn from interactions with their parents duringtheir own childhood and adolescence (see Conger,Belsky, & Capaldi, 2009; Belsky, Jaffee, Sligo, Wood-ward, & Silva, 2005). Indeed, previous researchusing the same data as the current study demon-strates intergenerational continuity in parenting(e.g., Conger, Neppl, Kim, & Scaramella, 2003;Scaramella & Conger, 2003), although none of theseprevious studies examined continuity in parentalcommunication styles as in this study. Certainly,evidence suggests continuity over discontinuity inparenting across generations (Belsky et al., 2005;Campbell & Gilmore, 2007; van IJzendoorn, 1992).Thus, as adolescents transition to adulthood andbecome parents, they likely adopt communicationstyles similar to those of their parents. This isan important addition to the basic investmentperspective because types of learning promoted byfamily SES may shape interpersonal processes

affecting intergenerational continuities. Consistentwith the predictions for G1 and G2, we also proposethat G2’s educational attainment will predictresponsive communication to their (G3) young chil-dren (path e).

The final step in the investment model (Figure 1)involves influence of G2 educational attainment andresponsive communication on G3 children’s recep-tive vocabulary. Receptive vocabulary is defined asthe ability to comprehend words through listeningor hearing (Dunn & Dunn, 1981). Although nearlyall children learn to understand and producelanguage, the quality and quantity of languageacquisition seems dependent on environmental cir-cumstances. During early childhood the diversityand complexity of the words parents utter to chil-dren seem to positively influence children’s vocabu-lary development (Bornstein, Haynes, & Painter,1998; Hart & Risley, 1995; Huttenlocher, Haight,Bryk, Seltzer, & Lyons, 1991). Early vocabularydevelopment may result at least in part from paren-tal investments in communicating with children, asreflected by path g. Previous evidence indicates par-ents with higher educational attainment use morewords and take on a more supportive style of teach-ing when interacting with children (Duncan &Magnuson, 2003; Richman, Miller, & LeVine, 1992).Because we cannot be certain this one form ofinvestment entirely explains the association betweenG2 young adults’ educational attainment and G3children’s vocabulary development, we also includea direct path (f) between these two variables.

To summarize, this study sought to evaluate thehypothesized pathways in the family investmentmodel (Figure 1) with a third-generation sample.This involves intensive focus on mechanisms of in-tergenerational continuities in SES and parentalcommunication and the consequences of SES andparental investments on child development thanprevious studies with this data (e.g., Schofieldet al., 2011). The following analyses addressed fourpredictions:

1. G1 parents with more education and incomewill have children who obtain more education,and this association will be accounted for, inpart, because parents with more education andincome will demonstrate more clear andresponsive communication styles with theirchildren.

2. G2 adolescents who go on to achieve highereducational attainment will have children withmore advanced vocabulary development,partly because they will exhibit clear and


responsive communication patterns wheninteracting with their children.

3. G1 parents with more income and educationwill have adolescents who grow up to commu-nicate responsively and clearly with their G3children, with this parental communicationstyle modeled from a similar style displayedby the G1 parents and partly influenced bygreater educational attainment by the G2 ado-lescents.

4. G1 parents with greater income and educationwill have G3 grandchildren who exhibit moreadvanced vocabulary development, with thisintergenerational link being partially shapedby the greater educational attainment of theG2 offspring of G1.

Method

Participants

Participants drew from the Family TransitionsProject (FTP), a prospective, longitudinal study of559 target youth, their families, and selected closerelationships. Initial interviews were conductedwith G1 and G2 participants between 1989 and1991, when G2 were either in seventh or ninthgrade. In the original sample, 451 adolescents camefrom two-parent families and 108 came from single-parent, mother-headed families. FTP participantswere recruited to examine effects of the economicdownturn in agriculture of the 1980s and wererecruited from eight rural Iowa counties. Given thatthere were almost no ethnic minority children liv-ing in these counties then (approximately 1% of thepopulation), all participants were White. Most fami-lies were characterized as lower middle or middleclass based on self-reported incomes.

Data were collected from G1 parents only duringG2’s adolescence. Investigators continued to assessG2 participants annually beyond their high schoolyears. To reflect changing focus on family transi-tions, G3 children of G2 target participants wererecruited to participate starting in 1997. Eligible G3children were the oldest biological child of the G2target participant, at least 18 months of age, andlived with the G2 target participant at least 2 week-ends a month. On average, 90% of the G2 targetparents with eligible children agreed to participatein annual assessments with their G3 child. G3 chil-dren recruited between 1997 and 2003 were eligiblefor this study. Only three-generation families withdata available during the adolescent period, theearly adult period, and their child’s preschool years

(i.e., 3 or 4 years old) were included in the presentanalysis. By only including preschool-aged children,we were able to measure vocabulary during a devel-opmental period allowing for valid assessments.

Of the 147 families with a 3- to–4-year-old G3child, 139 had completed the receptive vocabularyassessment and were eligible to be included in thestudy. Eight vocabulary scores were missing eitherbecause of interviewer error or because G3 childrenwere uncooperative during assessments. On aver-age, G3 children were 36.8 months of age duringthe preschool assessment. Most of the G3 childrenwere boys (55% boys, 45% girls). G2 parents aver-aged 22.12 years of age at the time of their G3child’s assessment and included 39.8% men and60.2% women. Although marital status or cohabita-tion was not a criterion for participation, 64% ofparents were married and 21% were cohabitatingwith a romantic partner. The remaining 15% of par-ents were single. Most of the G2 parents (69.8%)were living with the other biological parent of theG3 child. All target G2s were custodial parents.

Procedures: Family of Origin Assessments of G1 andG2 (1991–1994)

Trained interviewers visited all participatingfamilies on two occasions during the 9th-, 10th-,and 12th-grade assessment periods (i.e., 1991, 1992,and 1994). Each visit lasted about 2 hr. During thefirst visit, family members completed a series ofquestionnaires, some of which included reports ofG1 educational attainment and household income.During the second visit, family members partici-pated in four structured videotaped interactions.Family interaction tasks were designed to evokevariations in qualities of family interaction. Onlythe family discussion task and the problem-solvingtask involved G1 parents and G2 adolescents andwere used in the present report. During the familydiscussion task parents and adolescents discussedtypical daily living issues such as parenting, schoolperformance, and household responsibilities(25 min). During the problem-solving task, familymembers attempted to resolve issues that werepresently a source of disagreement within the fam-ily (15 min).

Trained observers coded the family discussionand problem-solving interactions using the IowaFamily Interaction Rating Scales (IFIRS; Melby& Conger, 2001). Behavioral codes examining G1parents’ communication with G2 participantsduring adolescence (i.e., 9th, 10th, and 12th grades)were included in these analyses.


Procedures: Family of Procreation Assessments ofG2–G3 (1997–2003)

After G2 target participants graduated from highschool, they continued to participate annually.Beginning in 1997, G2 participants with an eligibleG3 child completed an additional 1 hr in homevisit with their child. Assessments with G3 childrenbegin when G3 children are between 18 and27 months of age (2-year-old assessment) and con-tinue on an annual schedule until children are7 years of age. Data for this study were collectedwhen the G3 children were approximately 3 or4 years of age. These assessments occurred for dif-ferent families at different points in time, depend-ing on when the G3 child was born. Thus, dataused in these analyses involving G3 could havebeen collected at any time from 1997 to 2003.

During the in-home assessments involving G3,children participated in many structured activities,some included in the present report. First, childrencompleted an 8-min free play activity. For the first3 min they played alone, and for the next 5 minwith the interviewer. This free play was not coded.Next, interviewers administered the Peabody Pic-ture Vocabulary Test–Revised (PPVT–R; Dunn &Dunn, 1981) to G3 children. Standard scores fromthe PPVT–R are used in analyses. G3 children alsowere videotaped with the G2 parent completingtwo commonly used structured activities; a puzzlecompletion task (5 min) and a clean-up task(10 min). In the puzzle task, G3 children were pre-sented with a puzzle too difficult for them to com-plete alone. As in other studies using similar tasksfor observing parent–child interaction (e.g., Keenan& Wakschlag, 2000; van der Mark, Bakermans-Kranenburg, & van IJzendoorn, 2002), G2 targetparents were instructed to let children complete asmuch of the puzzle on their own as possible, but tooffer any assistance they felt was necessary.

The clean-up task occurred at the end of the 60-min assessment battery. After the G3 child playedwith various toys for 3 min alone, the interviewerjoined the child and played for an additional 5 min.During the joint play, the interviewer dumped outall toys to standardize the amount of toys the G3children had to clean up. Once free play was over,interviewers retrieved the G2 target parent andinstructed the parent that the child needed to cleanup all the toys and, although the target parentcould offer any assistance necessary, the child wasto clean up independently as much as possible.Later, trained observers coded the puzzle andclean-up tasks using the IFIRS (Melby & Conger,

2001). Behavioral codes measuring G2 parents’communication with their G3 children during bothtasks were included in analyses.

Measures for the Family of Origin: 1991, 1992, and1994

G1 parent per capita income. During 1991, 1992,and 1994 assessments, G1 provided reports of theircurrent economic circumstances (see Table 1 fordata collection timeline summary). First, parentsreported on all sources of income including allmoney from jobs and investments. Second, a house-hold size score was created by summing all familymembers living in the home. Per capita income wascalculated by dividing total income by the numberof people in the home. The per capita incomes wereaveraged across the three assessments to create astable measure of G1 per capita income during G2’sadolescence. To avoid problems with estimationusing large numbers, G1 per capita income wasdivided by 1,000 for final analysis.

G1 parent education. During 1991, 1992, and 1994assessments, G1 mothers and fathers reported high-est level of education completed. G1 mother andfather education scores thus indicated total numberof years of education completed by each parent.Mothers’ and fathers’ highest levels of educationalso were averaged to create a single G1 parentaleducation score, indicating the average years of for-mal education completed.

G1 parental communication. The latent constructfor parental communication indicated the degree towhich parents communicated with adolescents in aclear, positive, and cogent manner. This measurealso evaluated the degree to which parents listenedto and responded to G2, thus promoting the com-munication and language use skills of G2. Three of22 dyadic interaction scales in the IFIRS (Melby &Conger, 2001) focus specifically on quality of com-munication from parent to child. These ratings weregenerated during the family discussion and prob-lem-solving tasks and were used as three separateindicators for this latent construct. Both the prob-lem solving and family discussion tasks includedthree to four family members: G1 fathers (whenapplicable), G1 mothers, G2 target adolescents, andone G2 sibling. Separate scores were originally gen-erated for mothers’ behavior toward target, moth-ers’ behavior toward sibling, and mothers’ behaviortoward father, for instance, and the behavior ofother family members were not considered whenassigning scores. For this study, only the ratingsbased on an individual parent’s behavior directed


toward the G2 adolescent were used in analyses. Allbehaviors were rated on a 9-point continuumranging from no evidence (1) to highly characteristic (9).The three behavioral rating scales used as indicatorsof the latent construct were (a) communication,(b) listener responsiveness, and (c) assertiveness.

The Communication scale measured the level ofG1 parents’ (mothers’ or fathers’) verbal expressiveskills as well as content of statements during verbalexchanges with G2. This scale is used to rate theparents’ ability to neutrally or positively expresstheir own point of view, needs, wants, and so on,in a clear and reasonable manner, and to demon-strate consideration of the G2 adolescents’ points ofview (Melby & Conger, 2001). Behaviors codedwithin the communication code include use ofexplanations, clarifications, reasoning, soliciting theviews of others that are considerate of the G2 par-ticipants’ points of view, encouraging explanationsand clarifications, as well as responding reasonablyto the ongoing conversation.

The Listener Responsiveness scale assessed thedegree to which G1 parents attend to, show interestin, acknowledge, and validate the verbalizations ofthe G2 through use of nonverbal backchannels andverbal assents. This scale rated the parents’ nonver-bal and verbal responsiveness as a listener to theverbalizations of the G2 through behaviors that val-idate and indicate attentiveness to the adolescent(Melby & Conger, 2001). Responsive listeners areoriented to the speaker, convey interest in theconversation, and make the speaker feel heard.

Finally, the Assertiveness scale measured qualityof G1 parents’ verbal presentation by evaluating the

degree to which G1 parents express themselves withconfidence and forthrightness while expressingpoints of view clearly. Specifically, this scale evalu-ated G1 parents’ ability to express themselvesthrough clear, appropriate, neutral or positive ave-nues using an open, straightforward, nonthreaten-ing, and nondefensive style (Melby & Conger, 2001).

Interrater reliability was computed separately foreach task by randomly selecting 25% of videotapesto be coded by a second observer (i.e., doublecoding). Intraclass correlations are used to assesinterobserver agreement, and agreement betweensingle scales like the three used in the current investi-gation range from .55 to .85 (Kerig & Lindahl, 2001).Twenty-five percent of the interaction tasks werecoded by two independent observers and theindicator scores demonstrated substantial interraterreliability (average intraclass correlation coeffi-cient = .87).

In addition to its demonstrated reliability, theIFIRS has been validated. First, convergent validityof the scales has been demonstrated when corre-lated with reports of similar behaviors from selfand other family members based on correlationaland confirmatory factor analyses (see Conger et al.,2002; Melby, Ge, Conger, & Warner, 1995). In addi-tion, the IFIRS has demonstrated predictive validitywith rural Iowa families and minority families fromthe South and Midwest (Conger et al., 2002). Melbyand colleagues report similar findings on thereliability and validity of the IFIRS (Melby, Bryant,& Hoyt, 1998; Melby & Conger, 2001).

Identical coding procedures were used acrossthe adolescent period for all assessments (i.e., 9th,

Table 1Summary of Data Collection: What, When, and From Whom

Construct

Family of origin: G2s’ adolescence Family of procreation:G2’s early adulthood

9th grade (1991) 10th grade (1992) 12th grade (1994) G3: 3–4 years of age

SESPer capita income G1 mother & fathera

self-reportsG1 mother & fathera


self-reportsNot included

Parental education G1 mother & fathera



self-reportsG2 self-reports

Parental communication Observational ratings:G1 mothers & fathersa

with G2

Observational ratings:G1 mothers & fathersa

with G2

Observational ratings:G1 mothers & fathersa

with G2

Observational ratings:G2 with G3

G3 Receptive vocabulary Intervieweradministered

aMost participating families were included the two biological parents of the G2 adolescents; however, one fifth of participating familieswere from single-parent households. The aggregate of mother and father data was used. If fathers were unavailable, only mother datawere used.


10th, and 12th grades). Data reduction involvedaveraging scores for each code across the two tasksand three time points separately for each parent.Mothers’ and fathers’ scores were significantly corre-lated within task. Because some families wererecruited when parents had recently experienced adivorce, no father data were available for 22% of G2adolescents. For initial modeling, G1 mothers’ andfathers’ scores were used separately and we evalu-ated whether parameter estimates were similar ordifferent by parent gender. When differences werenot found between parents, the mean of mother andfather scores was used as a composite variable in thefinal analyses. If data from fathers were not avail-able, then only mother scores were used.

Family of Procreation Measures: 1997–2003

G2 target parent education. When G3 childrenwere 3 or 4 years old, G2 participants reported theirhighest level of education to date. The G2 parentaleducation score reflects total number of years offormal education completed by the G2 target.

G2 target parental communication. Analysesincluded G2 target parents’ (either mother or father)communication measured when G3 were 3 or4 years of age. Observational tasks such as theclean-up and puzzle tasks have been used previ-ously to assess parents’ communication with pre-school-aged children (e.g., Landry, Miller-Loncar,Smith, & Swank, 2002; van der Mark et al., 2002).The same communication, listener responsiveness,and assertiveness codes used to measure G1 com-munication were used as the three indicators for G2target parents’ latent communication construct. Nomodifications were made to definitions for behav-ioral ratings and separate teams of coders rated G1and G2 parents’ communication. That is, whileparents’ behaviors and word choices may differwhen addressing a young child as compared to anadolescent, qualitative aspects of communicationstyle remained consistent with the manual.

Observers rated G2 target parents’ communica-tion, listener responsiveness, and assertivenessduring interactions with G3 children during thepuzzle and clean-up tasks. As with other studiesusing these observational tasks, only one parent(the G2 target, either a father or a mother) waspresent with the G3 child. All codes were rated onthe same as for G1, ranging from no evidence of thebehavior (1) to highly characteristic (9). The threeglobal behavioral ratings were averaged across thetwo tasks to create three indicators of G2 targetparents’ communication, listener responsiveness,

and assertiveness with G3 children. Two indepen-dent observers also coded 25% of the tasks to mea-sure interrater reliability (average intraclasscorrelation coefficient = .83). Different coders ratedG1 and G2 communication.

G3 child receptive vocabulary. The PPVT–R (Dunn& Dunn, 1981) was used to measure G3 children’sreceptive vocabulary. The PPVT–R consists of a ser-ies of words for which respondents are required toselect a picture best representing the word from aset of four drawings. Children must achieve a basal,or minimum, score demonstrating that they under-stand how to complete the test and are able to meetbasic test criteria. Children continue to identifywords until they get 8 or more incorrect in a single12-item block. One advantage of the PPVT–R is thatnorms have been created based on age. The averagescore for each age is set at 100 with a standarddeviation of 15.

Results

Prior to hypothesis testing, the current sample of139 G2s and their families was compared with theoriginal sample of 559 G2s on G1 SES and commu-nication. Analysis of variance procedures were usedto evaluate the extent to which these characteristicsvaried across participants from the current sampleversus nonparticipating members of the originalsample. The only statistically significant differencethat emerged involved G1 education; G2 targets inthe current study had G1 parents completing signif-icantly fewer years of education than nonparticipat-ing G2 targets (F = 6.84, p < .01; mean ofnonparticipating G1 = 13.72 years). This differencelikely reflects that adolescents and young adultswith parents with a lower than average level ofeducation tend to have children earlier (Scaramella,Neppl, Ontai, & Conger, 2008). The intergeneration-al subsample in the present analyses demonstratedno differences in terms of family income or inter-personal investments (i.e., G1 communication).

Means, Standard Deviations, and Correlations AmongStudy Constructs

Table 2 summarizes the M, SD, and correlationsfor study constructs. Combined scores for G1mothers and fathers were used. As expected, allcorrelations were positive and most were statisti-cally significant. For example, G2 education waspositively correlated with G1 income (r = .17) andG1 education (r = .31). G2 targets completed


slightly more education (M = 13.57 years, SD =1.73) than G1 parents (M = 12.92 years, SD = 1.46).Consistent with the theoretical model (Figure 1), G1education and income were positively correlatedwith G1 communication. Also consistent with themodel, G1 communication was significantly corre-lated with G2 education, G2 communication, andG3 receptive vocabulary. G2 education also wassignificantly associated with G2 communicationand G3 receptive vocabulary. Given this prelimin-ary support for several of the hypothesized path-ways in the theoretical model, the next step was toevaluate the full theoretical model depicted inFigure 1.

Evaluation of the Structural Equation Model (SEM)

SEMs were estimated using Mplus 6.1 (Muthén& Muthén, 1998–2010) and full information maxi-mum likelihood. The latter provides more consis-tent, less biased estimates than ad hoc proceduresfor dealing with missing data (Arbuckle, 1996;Schafer, 1997). We first evaluated a model that trea-ted G1 mothers’ and fathers’ education and com-munication as separate constructs. Because eachparent contributed to varying degrees to householdincome, income was not estimated separately byparent gender.

To determine whether mother and father effectswere significantly different, we estimated a modelwith corresponding paths constrained to equalityand another with these paths freely estimated. Chi-square values for competing nested models werecompared, and a nonsignificant difference in chisquare values indicated constrained parameterswere not significantly different. Each pair of pathswas tested separately and four of the five pairs ofpaths were not significantly different. That is,mother and father effects did not differ significantlyfor these four effects. A significant difference wasfound for the fifth pair in that income positively

and significantly affected mother’s communication,but not father’s. However, testing all five sets ofpaths simultaneously did not result in a significantdeterioration of model fit, indicating that overall,mother and father effects are not significantlydifferent. Given this and the limited utility of sepa-rating these effects, we present the results for themore parsimonious model with G1 mother andfather measures combined into G1 parent measuresas described earlier.

We conducted multiple group analysis to test forG3 child gender differences in the paths directlylinked to G3 vocabulary, as well as to test for G2 gen-der differences in all paths directly linked to G2constructs. Our results indicated no significant G3gender differences; however, there were significantdifferences between G2 males and females. Thus,models were estimated allowing separate estimateson parameters that differed significantly by G2 gen-der. When no significant gender differences werefound, a parameter was constrained to equality acrossgroups. Particularly noteworthy, even when a pathcoefficient is constrained to be equal across groups,the standardized estimates may differ for females andmales because of differences in variances.

Figure 2 presents the results of SEM evaluating thefamily investment model. Fit indices affirm that themodel demonstrated adequate fit with the data: Theroot mean square error of approximation (RMSEA) isless than .05 and the comparative fit index (CFI) isgreater than .95 (Hu & Bentler, 1999). All factor load-ings were significant, in the expected direction and ofrelatively large magnitude (see Table 3).

Hypothesis 1: G1 parents with more educationand income will have children who obtain moreeducation, and this association will be accountedfor, in part, because parents with more educationand income will demonstrate more clear andresponsive communication styles with theirchildren.

Table 2Summary of the Correlations, Means, and Standard Deviations, for Final Study Variables

1 2 3 4 5 6 M SD

1. G1 education — 12.92 1.462. G1 income .41** — 6.59 4.673. G1 communication .27** .24** — 4.60 0.944. G2 education .31** .17** .21** — 13.57 1.735. G2 communication .23** .13 .35** .48** — 5.33 1.116. G3 vocabulary .18** .09 .16* .28** .48** — 93.84 15.51

*p < .05 (one-tailed test). **p < .05 (two-tailed test).


The results presented in Figure 2 indicate, consis-tent with predictions, G1 tended to use a moreresponsive and clear communication style with ado-lescents when parents had more education (b = .17,p < .05) or income (b = .17, p < .05). G2 adolescentswhose parents used a responsive communicationstyle tended to be more responsive in communicat-ing with their G3 children, both as mothers(b = .24, p < .05) and as fathers (b = .23, p < .05).Similarly, male adolescents whose parents hadexhibited more clear and responsive communicationattained more years of education (b = .37, p < .05).This pattern was not supported, however, for G2female adolescents. Also consistent with the model,adolescents of both sexes whose parents had moreeducation attained more education themselves(b = .27, p < .05). However, G1 income was notsignificantly associated with G2 educational attain-ment. Although simple correlational analysis indi-cated G2 adolescents whose parents had highereducational attainment exhibited more clear andresponsive communication with their children oncethey became parents, the findings of the SEManalysis suggest this link is accounted for by therelation between G1 parental communication andG2 adolescents’ eventual educational attainment.This notion was further supported by tests usingthe delta method to calculate the standard errors ofindirect effects (b = .12, p < .05, two-tailed tests;Sobel, 1982).

Hypothesis 2: G2 adolescents who go on to achievehigher educational attainment will have childrenwith more advanced vocabulary development,

partly because they will exhibit clear and respon-sive communication patterns when interactingwith their children.

G2 educational attainment did predict their levelof responsive communication, which, in turn, wassignificantly associated with their children’s vocab-ulary (see Figure 2). Especially important, the previ-ously significant correlation between G2 parents’educational attainment and G3 vocabulary (r = .28,Table 2) became nonsignificant when controlling fordegree of responsive communication. Furthermore,the test of the indirect effect of G2 educationalattainment on G3 vocabulary via their level of clearand responsive communication was significant (G2males, b = .18; G2 females, b = .21). Taken together,these results indicate G2 parents’ communicationstyle with their children mediated the positive linkbetween their level of education and G3 vocabularydevelopment, consistent with the investmenthypothesis.

Hypothesis 3: G1 parents with more income andeducation will have adolescents who grow up tocommunicate responsively and clearly with theirG3 children, with this parental communicationstyle modeled from a similar style displayed bythe G1 parents and partly influenced by greatereducational attainment by the G2 adolescents.

Support for this hypothesis was mixed. Theresults depicted in Figure 2 indeed indicate G1parents who demonstrated clear and responsivecommunication patterns during G2’s adolescencehad offspring who, as parents, tended to use similarcommunication patterns with their G3 children.G1 educational attainment, on the other hand,seemed to predict G2 parental communication styleprimarily through G2 educational attainment. Sucha pattern indicates socioeconomic factors in G1predict the degree to which parents present a

G2Parental

Communication

.27**/.27**

.17*/.17*

.37**/.02

.07/.07

.44**/.44**

.23**/.24**.41**/.47**

G3Receptive

Vocabulary

G2Parental

EducationG1

Education

G1Parental

Communication

.41**/.41**

.17*/.17*

-.01/-.01G1

Income

Figure 2. Results of the structural equation model evaluating thefamily investment model.Note. Standardized estimates for G2 males are left of the slash andto the right for G2 females (male or female). Coefficient in boldindicates significant differences between G2 males and females,v2 = 89.852, df = 78, comparative fit index = 0.982, root meansquare error of approximation = 0.047, *p < .05 (one-tailed test)**p < .05 (two-tailed test).

Table 3Standardized Factor Loadings for the Full Structural Model

Construct Indicator Factor loading

G1 communication Communication .97Listener responsiveness .75Assertiveness .92

G2 communication Communication .87Listener responsiveness .80Assertiveness .84


responsive parental communication style that willlikely be emulated by the G2 offspring once theyhave children.

Hypothesis 4: G1 parents with greater incomeand education will have G3 grandchildren whoexhibit more advanced vocabulary development,with this intergenerational link being partiallyshaped by the greater educational attainment ofthe G2 offspring of G1.

The findings support this hypothesis. G1 parentswith higher income and educational attainment hadgrandchildren exhibiting more advanced vocabu-lary development, with this relation explained byG2’s greater educational attainment and more clearand responsive parental communication (G2 males,b = .05; G2 females, b = .06). Furthermore, G1 par-ents exhibiting a more responsive parental commu-nication style also had G3 grandchildren withsignificantly higher vocabulary by way of G2responsive parental communication (G2 males,b = .09; G2 females, b = .11). A similar pattern wassupported regarding this indirect path from G1responsive communication style and G3’s moreadvanced vocabulary development through G2’sgreater educational attainment, but it was onlysignificant for G2 males (b = .07).

Evaluation of Alternative Models

Finally, a series of alternative models was con-sidered. We reestimated the model in a number ofways. First, we evaluated the impact of G3 chil-dren’s own communication style on their parents’communication style. Then, as G2 targets had chil-dren at different ages and G3 children’s age variedslightly within the sample, we reestimated themodel controlling for age of both G2 and G3 partic-ipants. The following section summarizes thesefindings.

First, we reestimated the model depicted in Fig-ure 1 considering influence of G3 children’s owncommunication patterns directed toward parents onparental communication patterns. Importantly, chil-dren’s communication was measured using thesame indicators of communication, listener respon-siveness, and assertiveness as with their parents. Totest children’s role in shaping parents’ communica-tion patterns, we added a latent G3 children’scommunication construct and added an additionalpath from children’s communication to G2 parentalcommunication. While results supported a statisti-cally significant relation between communication

patterns of G2 and G3 (b = .42, p < .01), inclusionof this path reduced the overall model fit, as indi-cated by a statistically significant chi-square,v2(56) = 104.50, p < .01, CFI = .94, RMSEA = .08.Importantly, including the additional path did notalter the pattern of significant findings or directionof relations reported in Figure 2. Thus, children’scommunication to parents does not account for orchange the results reported in Figure 2.

Next, we considered the influence of G2 and G3age on the overall results. Not surprisingly, G2 ageemerged as a significant predictor of both educa-tional attainment and communication patterns withG3 children. Again, controlling for G2 target parentage diminished model fit but did not alter the pat-tern of relations among any constructs. Similarly,when G3 children’s age was added as a controlvariable, no statistically significant paths resulted.Thus, neither G2 nor G3 participant age altered theset of findings reported in Figure 2.

Discussion

This study examined continuities in SES and itsconsequences across three generations. The familyinvestment model guided the analysis (e.g., Conger &Donnellan, 2007) and results present a complex pic-ture of intergenerational relations between SES andadolescent and child development. In particular,structural equation analyses revealed positive asso-ciations between G1 parents’ SES and interpersonalinvestments in their children. Both parental incomeand education predicted responsive communicationto G2 during adolescence, which, in turn, predictededucational attainment, but only for G2 sons. Inaddition, G1 educational attainment was signifi-cantly associated with educational attainment of G2sons and daughters.

Moreover, as expected, G2 educational attainmentwas associated with their communication style withtheir G3 children, which, in turn, predicted moreadvanced G3 vocabulary development. In contrast toexpectations, parental educational attainment wasnot directly associated with children’s vocabularyand results indicated that G2 target parents’ degreeof clear and responsive communication with theirchildren mediated the association between their edu-cation level and their children’s vocabulary. Thisfinding is consistent with the most conservative pre-diction from the family investment model hypothe-sizing parental investments will completely accountfor expected association between parent SES andchild development. The following sections will first


discuss the results related to the family investmentmodel and then describe the limitations, strengths,and the implications of these results for futureresearch.

An Intergenerational Evaluation of the FamilyInvestment Model

The family investment model proposes highercompared to lower SES parents have childrenexhibiting more academic success at school (e.g.,Considine & Zappalà, 2002; Linver et al., 2002)and more likely to pursue postsecondary education(e.g., Duncan et al., 1998; Sandefur et al., 2006).Theoretically, benefits accrue because higher SESparents have time for more interpersonal invest-ments and the financial means for more materialinvestments. In this investigation, parents’ use ofclear and responsive communication with their chil-dren was hypothesized to be an important parentalinvestment through which SES would shape devel-opment across generations. Use of a third-genera-tional design allowed for a direct evaluation of thefamily investment model as well as a within familyreplication of the investment process.

Interesting findings emerged regarding parent–adolescent relationships between G1 and G2, whichmay establish the foundation for later parent–childrelationships between G2 and G3. First, we antici-pated that G1 SES would predict G2 human capitalformation both in terms of educational attainmentand eventual parenting skills. Both G1 income andeducation predicted G1 responsive communication,which, in turn, predicted communication quality ofG2 offspring. These results add a new marker ofhuman capital (i.e., responsive communication) tooutcomes previously considered in tests of the fam-ily investment model (e.g., Schofield et al., 2011).

With regard to prediction of G2 educationalattainment, results are more complex. G1 educa-tional attainment predicted G2 educational attain-ment whereas their income did not. This isparticularly relevant for professionals seeking tobolster educational opportunities for low-incomechildren and adolescents. With the financial aspectof SES less predictive than parental education, wehave further evidence that poverty need not be des-tiny. Low income presents an obvious practicalobstacle to educational attainment, but financiallimitations may be overcome when parents valueacademic accomplishment and encourage offspringto pursue postsecondary education. Our findingssupport G1 parents’ education, then, as the key ele-ment of SES molding later generations’ academic

readiness and achievement. Parental educationappears more relevant to later generations’ successwhen considering its relation to parental communi-cation.

G1 parents’ personal investments, in the form ofclear and responsive communication, were signifi-cantly associated with G2 educational attainment atthe bivariate level, with this association only reach-ing significance for G2 sons in SEM analyses.Future research explicitly testing potential sexdifferences in the relation between parental commu-nication and educational attainment is clearly war-ranted. Some research indicates that family andparenting factors are associated with adolescenteducational achievement and attainment differentlyfor boys than for girls (Deslandes, Bouchard, &St-Amant, 1998; Hindin, 2005). Girls possibly profitmost from examples parents provide via their owneducational attainment. Boys, though, may beaffected both by parents as models and by interper-sonal investments received from higher SESparents.

In contrast, G2 clear and responsive communica-tion fully mediated the association between theireducational attainment and their G3 children’svocabulary in all estimated models, suggesting suchan interaction style may play a critical role in main-taining intergenerational continuities in academicreadiness and success. This result provided strongerthan expected support for the investment hypothe-sis inasmuch as there are many material and inter-personal investments that higher SES parents maymake to encourage the competent development oftheir children. For instance, parental education isfrequently proposed to have a powerful relationwith children’s cognitive ability even during thetoddler years (e.g., Roberts et al., 1999). Similarly,an accumulation of social risk has been found toindirectly undermine language development duringinfancy by affecting parents’ ability to establish anenvironment supportive of learning and languagegrowth (Burchinal, Vernon-Feagans, Cox, & KeyFamily Life Project Investigators, 2008). Given thedifference in developmental stages between G3 chil-dren and G2 young adults, finding the relationbetween G2 education and G3 vocabulary is medi-ated by G2 communication patterns makes sense.That is, vocabulary development has been found topredict later educational attainment, but actual edu-cational achievement is far off for G3. Nonetheless,the path to ultimate educational attainment beginswith transition to kindergarten or first grade. Amore successful transition is enhanced with moreadvanced vocabulary skills and a positive example


set by parents. The combination of advanced vocab-ulary skills and parents’ use of responsive commu-nication may place children on a trajectory ofincreasing academic competence, thereby affectingtheir future educational attainment.

Importantly, parents are not the only adults whocommunicate with preschool-aged children. Youngchildren also may engage in verbal interchangeswith other family members, neighbors, and child-care providers. Frequency and quality of these ver-bal exchanges may influence children’s vocabularydevelopment. In fact, quality of out-of-home childcare predicts early cognitive and language develop-ment even when controlling for family characteris-tics (Burchinal et al., 2000; NICHD Early ChildCare Research Network, 2005). Interestingly, moreaffluent parents are more likely to secure high qual-ity child care and may be better able to invest inout-of-home experiences enhancing children’svocabulary and academic competencies.

In this study, parents’ clear and responsive com-munication emerged as a mediator of the intergen-erational transmission of educational attainmentand vocabulary development. These results areconsistent with previous work linking responsiveparental communication with more enriched vocab-ularies during early childhood (e.g., Hart & Risley,1995; Huttenlocher et al., 1991; Weizman & Snow,2001). However, our parental communicationmeasure was based on global ratings of parents’communication during videotaped structured par-ent–child interactions rather than typical measure-ment of communication patterns involving countingthe variety of words parents use (e.g., Bornsteinet al., 1998) or the quantity of verbalizations (e.g.,Hart & Risley, 1995; Huttenlocher et al., 1991). Inother words, coders rated qualitative aspects ofparental dialogue. Higher communication scoresreflected clearer and more assertive speech thatbuilds upon and responds to the statements andinterests of the child. Such a pattern may be effec-tive in teaching adolescents how to communicateclearly and effectively in academic and career set-tings and may have the added benefit of promotingvocabulary growth in the next generation.

Especially noteworthy, however, is that the cur-rent findings at least suggest a similar family invest-ment process across two different generations in thesame families. The G2 to G3 findings indicate higherSES in the form of parental education promotesparental investments in children’s learning process.Importantly, these investments appear to explainthe link between parental education and aspects ofcognitive and language development. Consistent

with the family investment model predictions, G1parental investments may have initiated develop-mental trajectories influencing G2 educationalattainment. That is, the relation between G1 SESand G2 educational attainment likely began withsimilar parental investments when G2 were youngchildren, not just through patterns of G1 communi-cation during adolescence. Nevertheless, these find-ings demonstrate that parental investments mediatethe impact of SES on academic or cognitive out-comes for adolescents in a process similar to that foryounger children. In that sense, these results pro-vide a unique contribution to our understanding ofSES and family investment process.

Limitations and Future Directions

Several limitations are noteworthy. First, thesample is unique. Intergenerational studies areexpensive and require ongoing participation.Indeed the present sample has participated fornearly 20 years. Moreover, only G2 participantswith a child 18 months or older and who werewilling to complete an additional interview wereincluded. Consequently, the youngest parents inour sample are disproportionately represented.Given that this study is ongoing, we expect to repli-cate these findings as the number of participatingG2 parents increases. Second, the observationaltasks used to measure communication were of shortduration in specific contexts. Although G1 commu-nication was based on three 35-min interactionsover a 4-year period, the G2–G3 interactions lasteda total of 15 min. Replication is clearly needed.Possibly, some of the findings reported here involvegenetic mediation, although a recent study foundno evidence for genetic influence on sensitive par-enting (Fearon et al., 2006) and McGuire (2010)recently reported observational measures of parent-ing of the type used in this study demonstrate littleif any evidence of heritability. Nonetheless, geneti-cally informed research designs will need to bepursued in the future to address possible geneticinfluences on these processes.

Third, the sample consisted primarily of Whitefamilies in rural areas, potentially limiting the gen-eralizability of results. Replications with minorityand rural families will increase confidence in theseresults. Fourth, the investigation only assessed oneaspect of language competence, receptive vocabu-lary. Although strongly related to measures ofexpressive language and full-scale IQ (Kutsick,Vance, Schwarting, & West, 1988), the PPVT–R onlymeasures the number of words children recognize.


Additional research relating parental SES and com-munication to other measures clearly is warranted.Furthermore, we only considered one type ofparental investments, namely, quality of parentalcommunication. Previous research using data fromthe same sample has indicated that emotional andmaterial investments also impact G3 children’sadjustment (e.g., Schofield et al., 2010). Otherfactors, such as overall involvement, sensitivity,and responsiveness are not limited to communica-tion, and breadth of vocabulary also may accountfor observed associations and likely covary withour communication measure.

Finally, as with other developmental research,our findings may be culture specific. For example,contemporary American culture places value oneducation for both males and females. It is likelythat results would differ with families living withina culture prohibiting or limiting educational oppor-tunities for females. The fact that our study partici-pants exhibited highly similar levels of educationalattainment for males and females is probably areflection of Western cultural standards and oppor-tunities afforded to females.

Despite limitations, results of this study indicatebenefits of parental investments in the form of clearand responsive parental communication extendbeyond family of origin to influence features ofparental behavior and vocabulary developmentwithin the next generation. More generally, SES inone generation was not only associated with cogni-tive development and educational achievement inthe next generation, SES also appears to promotepatterns of communicating that foster outcomesthat are adaptive in modern Western academicsettings.

Future research also would benefit from study-ing vocabulary and other language aspects oncechildren enter kindergarten. For example, experi-ences within formal academic settings may compen-sate for situations in which parents do not makesufficient interpersonal investments in vocabularydevelopment. In some cases children who lagbehind peers in vocabulary development becausethey are exposed to less verbal communication athome or because parents have language barriersinterfering with ability to help children may catchup once they interact with others at school (seeConnor, Morrison, & Underwood, 2007). Possibly,parents with more education also are more familiarwith the educational system and engage in commu-nication patterns that are valued in a school setting.Less well-educated parents may communicate withchildren in ways consistent with behaviors valued

within their communities, but these styles may beless compatible with a school setting. Alternatively,such children may enter school at a disadvantageand continue to struggle and fall behind over time(see Lloyd & Hertzman, 2009). Following childrenlongitudinally from the preschool period throughearly school years would clarify how quality ofearly parent–child communication influences chil-dren’s academic adjustment and would aid inter-vention efforts to maximize children’s academicsuccess.

Future studies considering measures of other typesof human investments are also needed. Although weconsidered qualitative aspects of parents’ communica-tion with children, quantity of time spent withchildren and number of learning resources availableto children also may influence children’s vocabularygrowth and school readiness more broadly. In addi-tion, children’s exposure to educational media, liketelevision and video games, may augment parents’efforts to enrich verbal communication. Importantly,these results indicate qualitative features of parents’communication patterns may have both within andacross generational influences.

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