Toddler Vocabulary Production in Low-Income Families - Essay Example

Running head: CRITICAL APPRAISAL Critical Appraisal of a Published Research Paper: Pan, B. A., Singer, J. D., Snow, C. E. and Rowe, M. L. (2005). Maternal correlates of growth in toddler vocabulary production in Low-Income Families. Child Development 76, 763-782 Foster Dampare-Offe Student ID: 14034994/1 Sheffield Hallam University Module: Research Methodology 1 Award: MA Education (a) Summary of the paper: The objective of this was to investigate predictors of growth in toddlers’ vocabulary production between the ages of 1 and 3 years. This was achieved by analyzing mother-child communication in 108 low-income families. Individual growth modelling was used to describe patterns of growth in children’s’ observed vocabulary production and predictors of initial status and between-person change. The results indicate large variation in growth across children. The most parsimonious model that explains the observed patterns in the growth of childrens vocabulary was a one which had an intercept, a linear growth rate term and a quadratic term (level 1) and had maternal lexical input, language and literacy skills and depression as the significant predictors (level 2). The observed variation was positively related to diversity of maternal lexical input and maternal language and literacy skills, and negatively related to maternal depression. Maternal talkativeness was not related to growth in children’s’ vocabulary production in the study sample. Finally, the authors discuss the implications of the examination of longitudinal data from this relatively large sample of low-income families. (b) Research questions addressed: 1. What are the patterns of growth in observed vocabulary production among children from low-income families between 1 and 3 years of age? 2. Are the rates of change in children’s observed vocabulary production related to maternal communicative input, maternal education, maternal language and literacy skills, or maternal depression, controlling for child gender and birth order, maternal age, family income, and family participation in an intervention program? (c) Annotated Glossary of key terms: CES-D: The Centre for Epidemiologic Studies –Depression (CES –D; Radloff, 1977) scale, on which adults rate on a 4-point scale the frequency with which they have recently experienced 20 depressive symptoms Cross-sectional study: A study that does not follow the same individuals over time, but rather examines sequential classes consisting of individuals belonging to the same age class. Cumulation assumption: The assumption that once a child acquires the use of a word, it is never lost Child Abuse Potential: An inventory was designed primarily as a screening tool for the detection of physical child abuse by protective services workers in their investigations of reported child abuse cases (Milner, 1986) Child Factors: Factors that are intrinsic to a child, i.e. variables that are not influenced by experience, or environmental input CHILDES: Child Language Data Exchange System (CHILDES; MacWhinney, 2000) is a system of transcribing, coding and storing information pertaining to communication in children, notably in the form of words and gestures Dyad: An individual mother-child pair, treated as a single behavioural unit for study Early head start: A program within Head Start that promotes healthy prenatal outcomes, promotes healthy family functioning, and strengthens the development of infants and toddlers beginning as young as newborn infants. Environmental / input factors: Factors that are not intrinsic to the child, but are received as input from the environment Head Start: A program of the United States Department of Health and Human Services that focuses on assisting children from low-income families. Individual growth modelling: This is a statistical method of analyzing data by fitting the data to various candidate models, represented as growth equations. The growth equations describe the dependant variable (in this case, the child’s vocabulary at a given wave) for each individual as a function of the independent variables, and the process of fitting the data generates estimates for the coefficients, or parameters. Joint attention episodes: Episodes wherein both the mother and child have their attention, as determined by preconceived conventions, focussed upon the same object / event Longitudinal Study: A study that follows the same individuals over a period of time Median: The value below which (above which) 50% of the observations occur Multi-level model: A multi-level model is a variant of individual growth modelling. In this case, the individual growth model consisted of two levels: the Level 1 model described the change in vocabulary over time within an individual child, and the Level 2 model pertained to the between – child variation, and sought to describe this variation as a set of equations relating the Level 1 parameters to the predictor variables Pointing Gesture: Any use of the index finger by mother or child to point to a person or object. Shift in object being pointed at constituted a new instance of pointing Range: The difference between the maximum the minimum values in the sample Token: The total number of words spoken by the subject (mother/child) during the 10-min observation period Type: The number of unique words spoken by the subject (mother/child) during the 10-min observation period WAIS-R: Wechsler Adult Intelligence Scale - Revised or WAIS-R is a general test of intelligence (IQ), published in February 1955 as a revision of the Wechsler-Bellevue test (1939), standardised for use with adults over the age of 16. Wave: One of three instances wherein the authors videotaped interactions of the mother-child dyad. The three possible instances corresponded to the child ages of 14, 24 and 36 months, respectively. WJ: The Woodcock-Johnson test is a standardized neuropsychological test designed so the performance on the task can be linked to specific neurocognitive processes. (d) Context of the paper: Variation in the Development of Vocabulary Previous studies had shown a large amount of variation in the vocabulary of children in the age groups of 1 – 3 years (Fenson et al., 1994). However, it was unclear as to how much of this variation could be attributed to differences in the age of onset of vocabulary growth, and how much to differences in the rate of vocabulary growth. Longitudinal Studies A small number of longitudinal studies of child vocabulary growth had been conducted. Notable among the findings was that growth started with a period of slow word accumulation, followed by a prolonged period of accelerated word learning, beginning somewhere between 14 and 22 months (Goldfield and Reznick, 1990). However, these studies suffered from several lacunae. The most common shortcoming of longitudinal studies was the small sample size (Goldfield and Reznick, 1990; Brown, 1973; MacWhinney, 2000). While Hart and Rizley (1995) studied 42 children, only 6 of these came from low-income families. Factors Influencing Vocabulary in Children Two categories of factors influencing vocabulary development in children had been previously identified. Individual factors formed the first category and included gender (Bauer, Goldfield, & Reznick, 2002; Bornstein, Haynes, & Painter, 1998; Fenson et al., 1994; Huttenlocher et al., 1991) and birth order (Hoff-Ginsberg, 1998; Goldstein and Resnick, 1990). Environmental or input factors formed the second category and included amount of speech directed by parents towards children (Goldstein and Resnick, 1990; Hoff-Ginsberg, 1991; Hart and Rizley 1995). Vocabulary Development and Family Income Previous studies had shown that children from low income families are at a disadvantage with respect to vocabulary development compared to their middle income peers (Vernon-Feagans, 1996) and that this disadvantage can have long-lasting negative effects (Snow, Burns, & Griffin, 1998). Parents from low-income families tended to direct less speech to their children (DeTemple & Snow, 1996; Pan & Rowe, 1999). These results underlined the need for more studies on factors influencing child vocabulary development in children from low-income families. Other Factors Previous research has shown that mothers experiencing more stress and depression talk less to their children (Lovejoy et al., 2000). However, socioemotional aspects of mother-child interactions have been less widely studied as predictors of child language development (Belsky, 1984). Most work on the influence of communicative input on children’s vocabulary growth had examined only verbal input. However, nonverbal input such as pointing had previously been shown to influence child vocabulary development (Tomasello and Farrar, 1986). (e) List of Key Claims: 1. There exists a large amount of variation in vocabulary growth across children examined in the study. 2. The observed variation was positively related to the diversity of maternal lexical input and maternal language and literacy skills, and negatively related to maternal depression. 3. Maternal talkativeness was not related to growth in the children’s’ vocabulary production in the sample studied. 4. The most parsimonious model that explains the observed patterns in the growth of children’s vocabulary was a one which had an intercept, a linear growth rate term and a quadratic term (Level 1) and had maternal lexical input, language and literacy skills and depression as the significant predictors (Level 2). (f) Describe the methods used to gather and analyse information Data Collection Sample 108 mother-child dyads constituted the sample for this study. These were drawn from a larger study involving 146 dyads participating in a national longitudinal study of the effectiveness of Early Head Start (EHS). These dyads were videotaped on at least one of three occasions, or waves. Of these 108 dyads, 57 provided data for all three waves, 27 had data for only two waves, and 24 had data for only one wave. Sessions Each session involved a home visit, with the 10-minute observation period being videotaped. Dyads were provided with three bags containing a book and various toys. Mothers were asked to begin with a bag containing the book, then move on to each of the other two bags in turn. Transcription of videotapes The videotaped sessions were then transcribed using the CHAT conventions of the Child Language Data Exchange System (CHILDES; MacWhinney, 2000). Transcripts included both verbal and nonverbal (including pointing) behaviour by mother and child. A convention was established for the definition of ‘pointing’ events. Checks were constituted to ensure that all intelligible talk was transcribed and that transcription conventions were followed. Subsequent assessment showed that inter-observer reliability was 84% overall. Measures Child vocabulary was scored in the form of two measures: tokens and types. Tokens referred to the overall number of words produced, while types referred to the number of unique words produced. Maternal tokens, types, and the total number of pointing gestures used by the mother during the session were measured. Data on maternal education level were collected at baseline, reported in years. The vocabulary subscale of the Wechsler Adult Intelligence Scale – Revised (WAIS –R; Wechsler, 1981) and the letter –word identification portion of the Woodcock – Johnson Tests of Achievement (WJ; Woodcock, 1978) were administered to the mothers at baseline. The vocabulary subscale of the WAIS –R consists of 33 vocabulary words that participants are asked to define. The WJ letter –word identification test consists of 57 letters or words to be identified. Since maternal vocabulary and literacy measures were related to one another, they were standardized and combined using principal components analysis. The first principal component, which weighted the variables equally and explained 77% of the total variance in the original two variables, was chosen as the one measure of language and literacy skills. The Centre for Epidemiologic Studies –Depression (CES –D; Radloff, 1977) scale, on which adults rate on a 4-point scale the frequency with which they have recently experienced 20 depressive symptoms, was administered to mothers at baseline and at child ages 14, 24, and 36 months. Possible scores on the CES–D range from 0 to 60. Scores between 16 and 20 indicate mild depression, scores between 21 and 26 indicate moderate depression, and scores over 26 indicate severe depression. Data Analysis Descriptive statistics The first step involved generation of descriptive statistics, such as range, median, etc. for child tokens and types. To facilitate comparison with other work, descriptive statistics for cumulative word types at 24 and 36 months were computed. Developing a multilevel model of vocabulary growth Individual growth modelling techniques were used to analyse the longitudinal data. Since visual examination of individual trajectories revealed both linear and curvilinear trends, a wide range of curvilinear forms were comparatively examined. The best fitting Level 1 specification (i.e., the model with the lowest value on the -2 log-likelihood and Akaike Information Criterion statistics) included both linear and quadratic components. The parameters of the Level 1 model included terms representing the child’s true level of vocabulary production at 14 months, the child’s true instantaneous rate of growth at 14 months, and the child’s quadratic acceleration in growth over time. The values of these parameters were estimated. The between-person portion of the multi-level model for change (Level 2) used the individual growth parameters from the within-person (Level 1) model as outcomes. This enabled the authors to determine whether children vary in their initial status, instantaneous rates of change, or acceleration, and if so, what predicted that variation. The predictors included both time-varying variables such as mother tokens, mother types and mother points, as well as time-invariant variables such as maternal education such as maternal language, literacy, depression and controls. The maximum likelihood method was used to fit the multi-level model and estimate parameters, and the statistical significance of the various predictors was determined. (g) Describe the approach to enquiry of the authors The authors begin with clearly defined questions. The design of the study is tailored to address these questions by capturing as much of the variation as possible within the experimental constraints, both in the dependant variables (involving child vocabulary) and the predictor variables. To address the goal of examining growth in word use, rather than assumed vocabulary size, only word types produced in a given observation were counted. This decision was based on research suggesting considerable instability in children’s early vocabulary production (e.g., Bloom and Larhey, 1978). Given this instability, as well as the relative dearth of longitudinal studies examining growth in the variety of words children actually use, the authors opted to measure vocabulary production rather than assumed vocabulary size. The authors hypothesized that measuring growth in diversity of observed use might result in more linear growth than that documented earlier for cumulative vocabulary size. This hypothesis was later confirmed in this study. Advantages of the individual growth modelling approach One of the first advantages of using individual growth modelling is that the multi-level model for change is designed to deal with longitudinal data sets, such as the one used in this study, in which there are varying numbers of waves per person and variable spacing of these waves. Thus, all 108 dyads could be included in the analysis. Although dyads with fewer than three waves provided less, or no, information about within-person variation – and hence did not contribute to the estimation of variance components – they did contribute to the estimation of fixed effects (the structural portion of the individual growth model). The other advantage of the individual growth model approach is that it allowed the authors to examine the effects of predictors that are time-invariant as well as the effects of predictors that are time-varying. Because the individual growth modelling approach relies on a person-period data set, each predictor can, if appropriate, take on a specific value for each measurement occasion. The values of time-invariant predictors (e.g., child gender) are constant across the multiple records in the person-period data set. However, the values of the time-varying predictors are allowed to take on specific values they have at each measurement occasion. (h) Categorize according to purpose all references and citations made by the authors. The following constitute previous studies on child vocabulary development: Akhtar and Tomasello (2000), Bauer, Goldfield and Resnick (2002), Belsky (1984), Bloom and Lahey (1978), Bornstein, Haynes and Painter (1998), Bornstein et al. (1999), Brown (1973), Corkum and Dunham (1996), DeTemple, and Snow (1996), Fenson, Dale, Reznick, Bates, Thal and Pethick (1994), Goldfield and Resnick (1990), Hart and Risley (1995), Hoff (2003), Hoff and Naigles (2002), Hoff-Ginsberg (1990), Hoff-Ginsberg (1991), Hoff-Ginsberg (1998), Huttenlocher, Haight, Bryk, Seltzer and Lyons (1991), Iverson, Capirci, Longobardi and Caselli (1994), Iverson et al. (1999), NICHD (2000), Pan and Rowe (1999), Pan, Rowe, Spier and Tamis-LeMonda (2004), Pan, Rowe and Yont (2001), Pan, Snow and Willett (1993), Rescorla (1980), Rollins (2003), Snow et al. (1996), Tamis-LeMonda et al. (2001)Tomasello and Farrar (1986) , and Weisman and Snow (2001). The following are studies on the various maternal predictors used by the authors (also providing justification for inclusion of various candidate factors in the current study) Abidin (1995), Belle (1990), Breznitz and Sherman (1997), Iverson et al. (1999), Lovejoy et al. (2000), Murphy (1978), Pan et al. (1996), Radke-Yarrow et al. (1992), Radloff (1977), Rowe, Pan and Ayoub (in press) Vandell (1979) and Wechsler (1981). The following are studies that show an effect of the EHS programme on child vocabulary development: Love et al. (2002) The following are studies that describe the effect of socio-economic conditions on predictor variables used by the authors (justifying the need for a study on children from low income families): Belle (1990), Rowe (2000), Snow, Burns and Griffin (1998) and Vernon-Feagans, (1996). The following are sources for the statistical methods and other tools used by the authors: Bayley (1993), Hedeker and Gibbons (1997), Little and Rubin (1997), MacWhinney (2000), Raudenbush and Bryk (2002) and Singer and Willet (2003). The following are sources for measures and indices used by the authors: Milner (1986) and Woodcock (1978) Books used by the authors as part of the study Carle (1983) and Day (1996) (i) Identify and list with a brief explanation what you judge to be key references: 1. Fenson et al. (1994): This study was one of the early studies that documented the large amount of variation in child vocabulary development, and raised the question as to which variables influenced this variation. This question formed the motivation of the current study. 2. Huttenlocher et al. (1991): This study was groundbreaking as one of the first to apply individual growth modelling to the study of infant and toddler vocabulary growth. 3. Hart and Risley (1995): Prior to the publication of the paper under consideration, this study notable for being the longitudinal study on vocabulary growth with the largest sample size, and hence most reliable results. 4. Singer and Wille (2003): This text on longitudinal data analysis provided the tools for the study under consideration. Specifically, the multi-level modelling approach proved extremely useful in deriving conclusions from the authors’ data set. (j) Follow up as many of the key references as you can and give a brief report as to whether the reference fulfilled its purpose 1. Huttenlocher et al. (1991): Prior to the publication of Huttenlocher et. al. (1991), the prevailing view was that differences in child vocabulary were primarily due to inter-child differences in ability. This study was revolutionary in that it established, for the first time, that environmental, or input variables, play an important role in child vocabulary development. This paper claimed that the relation between amount of parent speech and vocabulary growth reflects parent effects on the child, rather than child-ability effects on the parent or hereditary factors. 2. Bornstein et al. (1997): This study evaluated maternal sociodemographic characteristics, personological characteristics, and vocabulary, as well as child gender, social competence, and vocabulary competence simultaneously in 126 children aged 1-8 and their mothers. Structural equation modelling supported several direct unique predictive relations: child gender (girls higher) and social competence as well as maternal attitudes toward parenting predicted child vocabulary competence, and mothers vocabulary predicted child vocabulary comprehension and two measures of mother-reported child vocabulary expression. The study concluded that individual variation in child vocabulary competence can be described as arising within a nexus of contextual factors both proximal and distal to the child. 3. Hoff (2003): This study addressed the question as to whether “children whose families differ in socioeconomic status (SES) differ in their rates of productive vocabulary development because they have different language-learning experiences” (1368). The study involved recording naturalistic interaction between 33 high-SES and 30 mid-SES mothers and their 2-year-old children at 2 time points 10 weeks apart. Upon transcribing these interactions, it was found that the high-SES children grew more than the mid-SES children in the size of their productive vocabularies, and that “properties of maternal speech that differed as a function of SES fully accounted for this difference” (1368). Thus, inclusion of this reference fulfils the purpose of justifying the need for studies on children from low income families. 4. Lovejoy et al. (2000): This study was a meta-analysis of 46 observational studies with the objective of assessing the strength of the association between depression and parenting behavior and to identify variables that moderated the effects. The study found that the association between depression and parenting was manifest most strongly for negative maternal behavior and was evident to a somewhat lesser degree in disengagement from the child. The association between depression and positive maternal behavior was relatively weak, albeit significant. Thus, this study fulfilled its purpose of providing a context for including maternal depression as a candidate predictor in the current study. 5. Tamis-Lemonda, Bornstein and Baumwell (2001): This was a previous longitudinal study, which examined the contribution of dimensions of maternal responsiveness (descriptions, play, imitations) to the timing of five milestones in childrens (N = 40) early expressive language: first imitations, first words, 50 words in expressive language, combinatorial speech, and the use of language to talk about the past. Events-History Analysis, a statistical technique that estimates the extent to which predictors influence the timing of events, was used. The study found that “maternal responsiveness at both ages predicted the timing of childrens achieving language milestones over and above childrens observed behaviours” (748). Inclusion of this study fulfils its purpose of demonstrating that previous longitudinal studies suffered from a paucity of sample size. (k) Assess the evidence available in the paper for the key claims made. 1. The results showed that the range of word types produced was 22 types at 14 months, 95 types at 24 months, and 122 types at 36 months. This establishes the .claim that children show a large amount of variation in vocabulary. 2. The final composite model (Model 6) had the lowest AIC and -2 log-likelihood scores. This indicates that among all the models considered, this model was the most likely to have generated the data. Model 6 had significant effects for maternal types, language and depression, the effects being positive in the first two cases and negative in the third. This effectively substantiates the primary claim of the paper, namely that the observed variation was positively related to the diversity of maternal lexical input and maternal language and literacy skills, and negatively related to maternal depression. 3. The lack of significant effects for maternal tokens in the multi-level model substantiates the claim that maternal talkativeness did not influence child vocabulary development in the sample studied. Critical Appreciation of the paper On the basis of the statistical analysis, assuming the veracity of the data, one can conclude that the key claims made in the paper are well substantiated. This study is notable for its use of multi-level modelling, due to which (a) the entire sample of 108 dyads could be utilized for data analysis, even though not all dyads participated in all three waves and (b) both time-dependant and time-invariant variables could be assessed as predictors. This has enabled the authors to demonstrate reliably a number of effects of different variables on child vocabulary development. On the other hand, there are severe limitations in extending the claims outside the study sample. These are primarily due to the paucity of temporal sampling points. Including more number of waves may cause the estimated parameters, especially in the Level 1 model, to change drastically. This means that the significance effects of the predictors may also change drastically, and thus the results may be an artefact of the poor temporal resolution of the sampling methodology. Further studies with higher temporal sampling resolution are thus needed to further establish the claims made in this paper. References Abidin, R. (1995) Parenting Stress Index (PSI). Parenting Stress Index professional manual (3rd ed.). Odessa, FL: Psychological Assessment Resources. Akhtar, N., & Tomasello, M. (2000). The social nature of words and word learning. In R. M. Golinkoff, K. Hirsh-Pasek, L. Bloom, L. Smith, A. Woodward, & N. Akhtar et al. (Eds.), Becoming a word learner: A debate on lexical acquisition (pp. 115 – 135). Oxford, England: Oxford University Press. Bauer, D. J., Goldfield, B. A., & Reznick, J. S. (2002). 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