The Relationship between Inattentiveness in the Classroom and Reading Achievement (Part B): An Explanatory Study KENNETH 1. ROWE, M.Sc.,

AND

KATHERINE S. ROWE, M.B., B.S., F.R.A.C.P.

Abstract. Findings from an explanatory study of the relationship between inattentiveness in the classroom and reading achievement are reported for a sample of 5,000 students (age, 5-14 years) drawn from a normal school population. Results of structural equation modeling showed that regardless of family socioeconomic status, age, and gender, students' inattentiveness had strong negative effects on their achievement as well as on their attitudes toward reading and reading activity at home. Moreover, the findings indicated strong reciprocal effects, suggesting that whereas inattentive behaviors lead to reduced achievement, reading achievement-mediated by attitudes and reading activity at home-leads to increased attentiveness in the classroom. The strategic implications of the findings are discussed. J. Am. Acad. Child Adolesc. Psychiatry, 1992,31,2:357-368. Key Words: inattention, reading achievement, home background factors, attitudes toward reading, structural equation modeling. The present study aimed to address the following research question: What are the magnitudes of the effect relationships between students' inattentive behaviors in the classroom and their reading achievement, mediated by home background factors and attitudes toward reading? At the outset, two major features of the question should be noted. First, the research evidence from studies examining factors affecting student learning has consistently identified the importance of home background, affective and behavioral factors that influence outcomes, and reading achievement in particular (Calfee and Drum, 1986; McGee and Share, 1988; McGee et aI., 1987; McKinney, 1989; Rutter, 1985; Topping and Wolfendale, 1985; Walberg and Tsai, 1985; Winter, 1988). The literature specific to the relationship between inattentiveness and reading achievement is considerable but is not reviewed here. However, the reader is referred to the brief review provided in the introductory section of the companion paper (Part A in this issue) and that presented in greater detail by Rowe (1991). Second, given that these factors do influence student outcomes, an explanatory model is proposed and tested for fit to relevant data obtained from a study among 5,000 students

Accepted May 20, 1991. Mr. Rowe is senior Policy Officer-Research, School Programs Division, Ministry of Education and Training, Victoria, Australia. Dr. Rowe is Lecturer and Physician, Department of Pediatrics, the University ofMelbourne, Royal Children's Hospital, Parkville, Victoria, Australia. The frank and willing assistance of the teachers who participated in the study is gratefully acknowledged. Thanks are also due to the "100 Schools Project" Steering Committee, Ministry of Education and Training, Victoria, for their encouragement and support, and to Neil Baumgart, Helen Praetz, Silvana Simmons, and Jackie Sykes for their invaluable assistance. Ken Ross provided valuable sampling advice. The comments made by two anonymous reviewers on an earlier version of this paper were most helpful. Financial support for the project was provided by the Commonwealth Resource Agreement. Reprint requests to: Ken Rowe, Senior Policy Officer-Research, School Programs Division, Ministry ofEducation and Training, Level 8 Rialto Towers, Box 4367, GPO Melbourne, Victoria 3001, Australia. 0890-8567/92/3102-Q357$03.00/0© 1992 by the American Academy of Child and Adolescent Psychiatry. J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

(age, 5-14 years), using structural equation modeling (SEM). This study was designed to examine the relationship between inattentiveness in the classroom and reading achievement, mediated by the putative effects of students' family socioeconomic background factors, reading activity at home, and attitudes toward reading. The reason for the use of SEM in this study was not only to meet the specific requirements of the above research question but also to avoid some of the methodological and analytical problems noted in Part A. To assist the reader who may be unfamiliar with SEM techniques, a relatively nontechnical overview of structural equation modeling, as illustrated by the LISREL model (Joreskog and Sorbom, 1989a), has been provided in the Appendix of Part A.

Two Explanatory Models Because the purpose of this study was to estimate the magnitudes of the effect relationships between students' inattentive behaviors in the classroom and their reading achievement, mediated by attitudinal and home background factors, the basic explanatory models proposed and tested in this study are schematically depicted in Figure 1. The recursive relationship shown in Model 1 posits that students' inattentive behaviors in the classroom have a direct effect on their reading achievement, mediated by the influences of attitudes toward reading and home background factors (family socioeconomic status (SES) and reading activity at home). The nonrecursive relationship shown in Model 2 posits a reciprocal influence between inattentiveness and reading achievement, mediated by the effects of home background factors and attitudes toward reading. Note that a recursive model is one in which all "causal" effects specified are "unidirectional," and all pairs of error terms in the model are assumed to be uncorrelated. A nonrecursive (or simultaneous equation) model is one that allows for reciprocal "causation" among variables and provides for the assumption that one or more pairs of error terms have nonzero correlations (Berry, 1984; Joreskog and Sorbom, 1989a). As a means of clarifying the hypothesized relationships,

357

ROWE AND ROWE

Modell

SOCIOECONOMIC

STATUS

Model 2 INATTENTIVENESS IN THE

CLASSROOM

HOME

ATTITUDES TOWARDS

BACKGROUND

READING

FACTORS

READING ACHIEVEMENT FIG. 1. Schematic representation of the hypothesized explanatory models.

the direction of putative effect relationships is given by unidirectional arrows. Estimation of the effects among the constructs, indicated by plus signs (+) and minus signs (- ), and their relative magnitudes constituted the major objectives of the study. Thus, Modell hypothesizes that while the effects among home background factors, attitudes, and achievement may be positive or negative, the influence of inattentiveness on attitudes and achievement is negative. Model 2 hypothesizes that, allowing for the direct mediating effects of home background factors and attitudes on achievement, inattentiveness leads to reduced reading achievement, 358

and higher levels of reading achievement lead to a reduction in inattentiveness (or to an increase in attentiveness). Method Sample Characteristics

To conserve space, specific details of the target populations and the sampling strata for the study are not reported here but are available elsewhere (Rowe and Griffin, 1988). In brief, however, the study was conducted in a stratified probability sample of 100 government and nongovernment J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

INATIENTIVENESS AND READING ACHIEVEMENT (PART B)

elementary and secondary schools, involving students at year levels 1,3,5,7, and 9, located in four education regions (two metropolitan and two rural). The sample design employed within each of the sampled strata was a three-stage cluster design in which schools were selected with probability proportional to size (PPS) at the first stage; one intact class selected randomly (at each year level), with PPS within each selected school at the second stage; and all students in the selected classes were included at the third stage. The level of sampling precision within each stratum involved the specification of sampling tolerances of ± 5% for 95% confidence limits for observed response variables, and estimates of variable means having ::; 5% of a respondent's standard deviation. To satisfy these sampling error constraints, it was calculated that a designed sample of at least 180 classes would be required (i.e., N = 180 X 20 = 3600). However, in an attempt to minimize the effects of possible nonresponse bias and missing data as well as for prima facie "representativeness" reasons, a more generous target sample of 280 classes (i.e., 5,600 students) was drawn. Procedure and Measures After invitations were submitted to sampled schools and their parent communities to participate in the project, prestudy briefing sessions for teachers from those schools were held to provide detailed information about the objectives, design, and administrative requirements of the study and to distribute the relevant data-gathering instruments. Two major instruments were used, both in the form of questionnaires. On the Student Record Form, two sets of indicators of home background factors were recorded. First, with the informed consent and cooperation of parents, family socioeconomic indicators were obtained that included the following: the number of years of mother's education and father's education; and mother's and father's occupational classification, as measured on the Australian Bureau of Statistics 8-point scale (Castles, 1986). Second, a measure of students' Reading Activity at Home was obtained from self-report responses on four Likert-type items, each measured on 4point rating scales: 1) Do you read books, magazines or newspapers at home?, 2) Do any of your family or friends read books or stories to you?, 3) Do you read books or stories to any of your family or friends?, and 4) Do you talk about books or stories you have read, with your family or friends? For each item, students were asked to respond in one of the following categories: Never, Not very often (defined as Once or twice per month), Often (once or twice per week), Every day (coded 0-3, respectively). Students' attitudes toward reading were indicated on three items: 1) Do you ENJOY reading?, 2) Do you find reading USEFUL?, and 3) How WELL can you read?, each measured on 5-point ordinal scales: Not at all, Not very much, Moderately, Quite a lot, and Very Much (coded Q--4). Data on reading activity and attitudes for younger students (5-6 years) were obtained by interviews conducted by classroom teachers. On the Teacher Record Form, a measure of students' J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

classroom inattentiveness was obtained from four teacherrated items, each measured on 5-point ordinal scales, following the bipolar format advocated and used by Kysel et aI. (1983). The psychometric characteristics of this domain and its constitutent items have been reported by Rowe and Rowe (1989). On the scale provided for each paired behavioral statement, teachers were asked to mark a category nearest to the statement that best describes typical behavior of the student. The relevant items are shown in Table 1. Scores on each item were coded 1 to 5, from positive to negative behavior. Reading achievement was assessed by students' scores on a reading comprehension test, and teacher ratings on a criterion-referenced profile of student reading behaviors. For 5-to 6-year-old students, the Primary Reading Survey Test, Level AA-Word Recognition (ACER, 1979) was administered. For students aged 7 to 14 years, age-appropriate subtests from the domain-referenced Tests of Reading Comprehension (TORCH) battery (Mossenson et aI., 1987) were administered. All students were rated by their teachers on the Literacy Profiles-Reading Bands (Griffin, 1990; Griffin and Nix, 1991)-a developmental, Rasch-scaled inventory of seven "bands," each consisting of multiple indicators describing reading behaviors. For each band of indicators, students receive a score of 0, no evidence; 1, beginning; 2, partial; and 3, complete evidence (that the indicators listed are consistently displayed by the student). Total scores for the seven bands range from 0 to 21. Before their administration, earlier versions of both questionnaire instruments (i.e., Student Record Form and Teacher Record Form, including the Student Behavior Inventory) were tried out extensively in the schools, the results from which were used to refine item nomenclature and presentation format. Analytic Approach With the student as the "unit of analysis," three types of analyses were conducted separately, for both girls and boys, in each of the four age groups of students. First, to provide the most conservative interpretation of the data, descriptive statistics for each indicator variable in their related latent domains were computed. Second, several preanalytic diagnostics and adjustments were made to the data, following suggestions made by Crano and Mendoza (1987), Brown (1989), Rowe (1989), and employed by Rowe (1991) and Rowe and Sykes (1989). This step entailed the analyses of confirmatory, one-factor, congeneric models to assess the measurement properties of the observed indicator variables for each related latent construct (Brown, 1989; Joreskog, 1971). Within substantive theoretical constraints, such procedures are designed both to purge the latent constructs of observed variables with unacceptably high levels of measurement error and to avoid the problem of multicolinearity (Pedhazur, 1982). Under a listwise method of deleting missing data, these one-factor models were analyzed using a weighted least squares method of parameter estimation in LISREL 7 (Joreskog & Sorbom, 1989b), based on a polychoric/polyserial intercorrelation matrix and an asymptotic covariance matrix of these correlations computed from 359

ROWE AND ROWE

1. Items Measuring Inattentiveness on the Student Behavior Inventory

TABLE

1. Cannot concentrate on any particular task; easily distracted 2. Perseveres in the face of difficult or challenging work

- - - - -

Can concentrate on any task; not easily distracted Lacks perseverance; is impatient with difficult or challenging work Easily frustrated; short attention span Purposeful activity

3. Persistent; sustained attention span 4. Aimless activity

2. Frequency Distribution of Student Sample by School Type, Age Group, and Genderb

TABLE

Age Group School Type Gov Elem NG Elem Gov Sec NG Sec Totals

5-6 Yrs

7-8 Yrs

9-11 Yrs

12-14 Yrs

F

M

F

M

F

M

519 221

448 203

497 304

467 217

476 200

486 222

740

651 1,391

801

684 1,485

aGov = Government school; NG = Nongovernment school; Elem b F = Female student; M = Male student.

PRELIS (JOreskog & Sorbom, 1988). (A rationale for this approach is provided in the Appendix to Part A in this issue). Third, an asymptotic covariance matrix (of the polychoric/polyserial correlations among the remaining indicators loading on the latent constructs) was computed for each age and gender subgroup of students and used as input to structural relations analyses of the proposed explanatory models (Fig. 1). (Note that separate models for girls and boys in each age group were tested but are not presented here in the interests of brevity). However, the separate solutions for male and female subjects in each age group were almost identical. Similarly, the results of the one-factor congeneric models computed to assess the measurement adequacy of the five latent variables are not presented, but each model (by gender and age group) was a "good fit" to the data, and no single indicator variable was discarded. Results Achieved Sample

Of the 100 schools originally invited to participate in the study, data on 5,092 students were received from 92 schools (71 primary, 15 postprimary, 6 P-12) for students grouped into the following four age categories: 5 to 6 years, 7 to 8 years, 9 to 11 years, and 12 to 14 years, drawn from 64 government schools and 28 nongovernment schools. Thus, from a target sample of 280 classes and 5,600 students, data were received from 256 classes on 5,092 students, representing 91 % of the target sample. Frequency details of the achieved student sample by school type, age group, and gender are shown in Table 2. With reference to sampling accuracy, the standard errors of the mean values for each of the variables of interest did not exceed ± 3.1%, which is well within the designed 5% limit of the targeted population value for determining the sampling frame. Data obtained on family socioeconomic variables indi360

Totals

676

708

F

264 133 397

1,384

M

F

M

310 125 435

1,492 725 264 133 2,614

1,401 642 310 125 2,478

832

5,092

= Elementary; Sec = Secondary.

cated that the mean number of equivalent full-time years of parents' education was 11.6 for mothers (SD = 2.9), and 12.0 for fathers (SD = 3.4). The data on parents' occupational classifications indicated that the proportions obtained in each of the eight categories were within 95% confidence limits for the Australian adult work force population (Castles, 1986). Descriptive Results on Response Variables

Descriptive statistics for the observed response variables of interest, by age group, are presented in Table 3. To assist interpretation, these variables have been grouped according to "membership" of their related latent constructs. With the exception of measures for students' reading Achievement, the data presented in Table 3 indicate considerable similarity with respect to the magnitudes of the response variable means (as well as their variances) across the four age groups. Moreover, the magnitudes of the internal consistency coefficients (ex's) for the student self-report scales (READACT and ATTITUDES) are respectable, in spite of the wide variation in age among the students and the limited number of constituent items in these scales. For the teacher-rated Inattentiveness items (INATTEN), the internal consistency coefficient (ex = 0.92) is high. To determine the proportions of unique variance in Reading Achievement (ACHIEVE) accounted for by the home background measures (i.e., SES and READACT), ATTITUDES and INATTEN, a composite score for reading Achievement was regressed onto each linear combination of the relevant manifest variables. For simplicity, the results of the regression analyses for the four age groups of students are presented graphically in Figure 2. From the data summarized briefly in Figure 2, it is clear that the family SES variables (i.e., mother's education, father's education, and father's occupation) accounted for very J. Am. Acad. Child Adolesc. Psychiatry, 3I :2, March I992

INATIENTIVENESS AND READING ACHIEVEMENT (PART B)

TABLE 3. Means and Standard Deviations for Response Variables by Age Group and Scale Reliability Statistics, Age Group Construct! Variable

7-8 Yrs

5- 6 Yrs

12- 14 Yrs

9-11 Yrs

X SD Reading Activity at Home (READACT) (Scale a = 0.85; standardized item a = 0.85)

X

SD

X

SD

READ 1 (Reading alone) 2.0 0.8 1.9 0.9 READ 2 (Read to by others) 1.4 0.9 1.4 0.9 READ 3 (Reads to others) 1.4 0.9 1.4 0.9 READ 4 (Discusses reading) 1.2 0.9 1.2 0.8 Family Socioeconomic Status (SES)b MEDUC (Mothers' education) 11.8 2.8 11.7 3.0 12.1 FEDUC (Fathers' education) 12.3 3.4 3.4 2.3 2.4 FOCC (Fathers' occupation) 5.2 5.1 Attitudes toward Reading (ATTITUDES) (Scale a = 0.74; standardized item a = 0.74) ENJOY (Enjoy reading) 1.0 3.0 1.0 3.0 3 .0 1.0 USEFUL (Reading is useful) 3.1 1.0 0.9 WELL (Self-assessment) 3.0 0.9 3.0 Inattentiveness (INATTEN) (Scale a = 0.92; standardized item a = 0.92) 2.5 1.3 Q 1 (Cannot concentrate) 2.5 1 .3 1.2 2.5 1.2 Q 2 (Lacks perseverance) 2.4 2.4 1.2 Q 3 (Short attention span) 2.4 1.2 Q 4 (Aimless activity) 2.1 1.1 2.2 1.1 Reading Achievement (ACHIEVE) TEST (Test score), 13.8 2.1 39.1 13.3 PROFILE (Profile score) 3.2 12. 5 3.6 9.8

2.0 2.0 1.4 1.2

0.8 0.8 0.9 0.8

2.1 1.5 1.3 1.3

0.8 0.9 0.9 0.8

11.3 11.6 5.1

2.9 3.5 2.3

11.6 11.8 5.2

2.9 3.5 2.4

3.0 3.1 3.0

1.0 0.9 0.9

3.0 3.0 3.0

0.9 0.9

2.5 2.5 2.4 2.2

1.3 1.2 1.2 1.1

2.6 2.5 2.5 2.3

1.3 1.2 1.2 1.2

48.8 14.9

13.6 3.6

60.4 17.1

14.1 3.8

X

SD

1.1

Note: Separate analyses for female and male students in each age group were computed but are not presented here. Although there were significant gender differences in favor of girls on all variables (with the exception of SES variables), the magnitudes of the intercorrelation estimates were very similar. aCronbach's a (internal consistency) coefficients are presented for self-report ordinal scales only. bBecause more than 48% of mothers indicated "Home duties," mother's occupation was excluded. , Scores for 5-to 6-year-old students are untransformed raw scores (maximum score 16). Scores for all other age groups are Rasch-scaled transformed scores from a subtest of the TORCH Test (Mossenson et aI., 1987).

small proportions of the variance in students' reading Achievement, ranging from 0.3% (7- to 8-year group) to 3.2% (12- to 14-year group). In contrast, Attitudes toward reading and Reading Activity at Home both contributed strongly to the proportion of variance in reading Achievement for each of the four age groups. However, the strongest influence, across all age groups, was from Inattentiveness, ranging from 13.4% (7- to 8-year group) to 22.9% (12- to 14-year group). Recursive Structural Equation Modeling To examine the influence of Inattentiveness in the classroom (lNATTEN) on Reading Achievement (ACHIEVE) as well as on the hypothesized mediating variables of students' Attitudes toward reading (Attitudes) and home background factors (SES and READACT), the recursive model (Model 1) depicted in Figure 1 was tested. Four models (one for each age group of students) were computed from the asymptotic covariance matrices of the polychoric/polyserial correlations for the response variables as given in Table 3. For these analyses, the LISREL method for Submodel 3b was used (Jareskog and Sarbom, 1989b, pp. 189-190). This general model contains only y (observed) and 11 (latent) variables. The major interest in this study concerned the estimation of the directional parameters of the ~s as shown in Figure 3. (The matrix specification of this model is given in the Appendix to this paper.) J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

Figure 3 illustrates the recursive model used to estimate the hypothesized covariance structure among the five latent variables (ellipses), for each of the four age groups. Table 4 presents the obtained parameter estimates for the measurement submodels (ellipses to rectangles) and for the structural submodels (ellipses to ellipses). To assist interpretation, completely standardized solutions are presented (i.e., true path analytic representations). Each variable has been standardized to unit variance, so that the A.S can be interpreted as standardized factor loadings for the latent variables on observed variables, and the structural coefficients (~) among the latent variables (unidirectional arrows) can be interpreted as path coefficients. For example, the solution for the 5- to 6year-old group indicates that one unit increase in INATTEN leads to a corresponding decrease of 0.269 units in ATTITUDES (~21) and a decrease of 0.719 units in ACHIEVE (P31)'

From Table 4, unless otherwise indicated, all parameter estimates of the models tested for the four age groups of students are 'significant beyond the p < 0.01 level, by univariate two-tailed tests. (It should be noted that statistical significance of a parameter estimate in a structural equation model refers to the original unstandardized parameter, divided by its standard error.) Additionally, all parameters were identified and the obtained goodness-of-fit indices for the models 361

ROWE AND ROWE

~ Family socio-economic status • Reading Activity at Home Percent of Explained Variance in Reading Achievement

25

lliill

Attitudes Towards Reading

m Inattentiveness in the classroom

20

15

10

5

Age Group in Years FIG. 2. Percenlage histogram showing proponions of explained variance in reading achievement for four age groups of students.

(i.e., GFI, AGFI, and RMR) indicate strong concordance between the data and the hypothesized model for each age group. (For an outline of the LISREL goodness-of-fit test statistics, refer to the Appendix in Part A.) Substantive interpretations of the solutions suggest several findings of interest. On the one hand, it is clear that the effects of family SES indicators on INATTEN, ATTITUDES, ACHIEVE, and READACT are weak and mostly insignificant (with the exception of SES on READACT for the 5- to 6-year-old group). On the other hand, the effects of INATTEN on ACHIEVE (P31) are substantial and negative, as they are on the mediating variables of AITITUDES (P21) and READACT (P41)' However, it is interesting to note that the strong effects of READACT on ACHIEVE (P34), mediated by ATTITUDES (P24 and P32), increase in magnitude across the four age groups, suggesting that Reading Activity at Home has a sustained and increasing impact on reading achievement as students progress through elementary and secondary schooling. In summary, the solutions to the recursive structural equation modeling of the data indicate that, regardless of age and gender, family SES indicators have little direct influence on measures of students' reading Achievement, Inattentiveness, Attitudes toward reading and Reading Activity at Home. However, Inattentiveness has strong negative influences on students' reading Achievement as well as on the mediating variables of Attitudes toward reading and Reading Activity at Home. Furthermore, the findings indicate that Reading Activity at Home has a significant influence on students' Attitudes toward reading and operates as a strong, mediating 362

influence between Inattentiveness and reading Achievement. Nonrecursive Structural Equation Modeling

To examine the interdependent effects between Inattentiveness (INATTEN) and reading Achievement (ACHIEVE), a nonrecursive structural equation model (Model 2) for each age group was tested. Because family SES had minimal effects, SES was excluded from the model. Figure 4 illustrates the hypothesized model, and Table 5 presents the standardized solutions for the model parameters for each of the four age groups of students. For simplicity of presentation, the factor loadings (AyS) for INATTEN and ACHIEVE are not tabulated (Table 4). Unlike the recursive relationship presented in Modell, in which all effects are unidirectional, Model 2 allows for estimation of the reciprocal effects between the latent variables of INATTEN (111) and ACHIEVE (112) and the direct effects of the observed mediating variables for AITITUDES and READACT on the latent variable of ACHIEVE. Thus, in Model 2 we have both observed "causes" (xs) and observed indicators (ys) of latent variables. However, to make meaningful conparisons of the reciprocal effects between INATTEN and ACHIEVE, the scales for 111 and 112 were fixed to be the same as Y3 and Y6, respectively. Hence, the Profile Score (Y6), like Y3, was rescaled as a 5-point ordinal scale. (The structural equations for this nonrecursive model are given in the Appendix.) The solutions to the models for each of the four age groups presented in Table 5 were successfully identified, J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

INATfENTlVENESS AND READING ACHIEVEMENT (PART B)

£8

1;3 TEST SCORE

Yg

/...93

PROFILE SCORE

Y9 £9

~~'d;; ~'~'~~ T~T ~T~T £14

£15

£16

£ 10

£ 11

£ 12

£ 13

FIG. 3. Recursive structural equation model.

and the goodness-of-fit indices indicate a "good fit" of the data to the hypothesized models. Unless otherwise indicated, the parameters are significant beyond the p < 0.01 probability level. The most notable finding is that while the reciprocal effects between INATTEN and ACHIEVE (~21 and ~d are both significant and negative, the effect of ACHIEVE on INATTEN (~12) is notably stronger for each age group. These results suggest that 1) inattentive behaviors in the classroom have a significant negative influence on students' reading achievement, and 2) reading achievement (mediated by the direct influence of AITITUDES and READACT) has a stronger effect on reducing inattentive behaviors. A corollary of 2) is that low reading achievement leads to high inattentiveness. An additional finding of interest is that the attitudinal indicators of reading enjoyment (ENJOY -Y21) and students' self-assessment of how well they read (WELL - Y23), have significant direct effects on ACHIEVE, but that students' assessment of the usefulness of reading (USEFUL - Y22) is only significant for the 12- to 14-year group. The effect pattern for the Reading Activity at Home indicators on ACHIEVE suggests that reading alone (READ 1 - Y24) has an increasing effect on ACHIEVE with age, whereas being read to (READ 2 - Y25) and reading to other family members (READ 3 - Y26) become less influential with age. The effect of discussing reading with others (READ 4 J. Am. Acad. Child Adolesc. Psychiatry, 3 J: 2, March 1992

Y27) on ACHIEVE is only significant for the 12- to 14-year

group. The correlations between INATTEN and ACHIEVE are tabulated to illustrate that although they indicate strong negative relationships, they cannot indicate alone the direction of effect. However, both the direction and magnitude of the interdependent effects are indicated by the path coefficients (~21 and ~12)' In sum, the results from the nonrecursive structural equation modeling of the data indicate a strong reciprocal relationship between inattentiveness and achievement. That is, although inattentiveness has a strong negative influence on reading achievement, the effects of achievement on inattentiveness, mediated by Reading Activity at Home and Attitudes toward reading have significant influences on reducing inattentiveness in the classroom. Discussion

The purpose of the present study was to examine the relationship between students' inattentive behaviors in the classroom and reading achievement, mediated by attitudinal and home background factors, which, to the best of the authors' knowledge, have yet to be studied in a covariancestructure context. It should be noted, however, that because the findings reported here are cross-sectional, the explana363

ROWE AND ROWE TABLE 4. Standardized Solution for Recursive Model by Age Group Age Group Parameter (Sample size with complete data) Measurement submodels (factor loadings) INATTEN AlI-QI AzI-Q2 A31-Q3 A41-Q4 ATTITUDES A5rENJOY ~rUSEFUL

A..,rWELL ACHIEVE A8rTE ST SCORE ~3 3-PROFILE SCORE READACT AlOrREAD 1 AlIrREAD 2 A12A-READ 3 A13rREAD 4 SES A14.5-MEDUC AI5.5-FEDUC A16.5-FOCC Structural submodel (path coefficients) INATTEN f321-ATTITUDES f331-ACHIEVE f341-READACT SES f315-INATTEN f325-ATTITUDES f335-ACHIEVE f345-READACT ATTITUDES f332-ACHIEVE READACT f33cATTITUDES READACT f334-ACHIEVE Goodness of fit statistics (df = 94) Goodness of Fit Index Adjusted Goodness of Fit Index Root Mean Square Residual

5-6 Yrs (N = 1,368)

7-8 Yrs (N = 1,350)

0.893 0.878 0.935 0.878

0.861 0.887 0.961 0.890

0.881 0.895 0.941 0.867

0.924 0.868 0.933 0.851

0.744 0.544 0.673

0.787 0.515 0.648

0.768 0.496 0.731

0.955 0.526 0.702

0.468 0.490

0.673 0.844

0.694 0.904

0.696 0.886

0.688 0.478 0.523 0.475

0.757 0.446 0.444 0.575

0.765 0.391 0.243 0.493

0.553 0.323 0.391 0.570

0.736 0.870 0.460

0.685 0.916 0.438

0.692 0.953 0.363

o .821

-0.269 -0.719 -0.262

-0.159 -0.343 -0.207

-0.388 -0.395 -0.264

-0.175 -0.539 -0.387

-0.088* 0.010* 0.078* 0.178

-0.039* 0.009* 0.017* 0.052*

-0.057* 0.031 * 0.075* 0.069*

-0.007* 0.064* 0.049* 0.040*

0.239

0.435

0.248

0.328

0.618

0.377

0.238

0.192

0.124

0.257

0.481

0.701

0.991 0.987 0.040

0.987 0.981 0.050

0.981 0.973 0.061

0.984 0.978 0.056

9-11 Yrs = 1,329)

(N

12-14 Yrs = 732)

(N

0.737 0.401

* Not significant.

tory models tested specify relations among variables at only one point in time. Under these circumstances, claims of causality cannot strictly be made, and, for this reason, the terms influence and/or effect have been used throughout. In the context of arguing for the common sense notion that "it takes time for causes to have effects," Gollob and Reichardt (1987, pp. 80-82) outline three principles about claims of causality in explanatory models: 1) Values of a variable are caused only by values of prior variables, 2) values of a variable can be caused by prior values of the same variable (i.e., autoregressive effects), and 3) the magnitude of effect sizes can vary as a function of the length of the time lag between a specified cause and the time at which its effect

364

is subsequently assessed. Additionally, there were some measurement limitations for the item indicators of the Reading Activity at Home variable. The four-point scale used was possibly too narrow. Perhaps a better measure, on a five-point scale, would have been Never, Once per month, Once per week, Two to three times per week, and Every day. Given such limitations, three major outcomes of the study are noteworthy. First, in terms of home background factors, the present findings support the argument of Share et al. (1983) that the common practice of using a single index of SES to measure home background, severely underestimates the relationship between the home and students' educational achievement. J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

INATIENTIVENESS AND READING ACHIEVEMENT (PART B) TABLE

5. Standardized Solution for Nonrecursive Structural Model by Age Group

Age Group Path Coefficient (Sample size with complete data)

5-6 Yrs (N = 1,368)

7-8 Yrs (N = 1,350)

9-11 Yrs (N = 1,329)

12-14 Yrs (N = 732)

ENJOY-ACHIEVE USEFUL Y23 WELL Y24 READ I-ACHIEVE Y25 READ 2 Y26 READ 3 Y27 READ 4 ~J2 ACHIEVE-INATTEN ~21 INATTEN-ACHIEVE Correlation INATTEN with ACHIEVE Goodness of fit statistics (df =42) Goodness of Fit Index Adjusted Goodness of Fit Index Root Mean Square Residual

0.186 0.095* 0.257 0.146 0.283 0.231 0.096* -0.633 -0.522

0.205 0.004* 0.278 0.245 0.182 0.161 0.086* -0.550 -0.295

0.295 0.089* 0.544 0.262 0.152 0.056* 0.042* -0.978 -0.927

0.747 0.109 0.410 0.314 0.112 0.193 0.125 -0.962 -0.879

-0.868

-0.480

-0.546

-0.605

0.996 0.991 0.030

0.996 0.992 0.032

0.996 0.991 0.028

0.994 0.987 0.038

Y21

Y22

* Not significant.

The present results are also consistent with the findings of Loney and Milich (1982) who have demonstrated that while low SES is associated with aggressive behaviors in childhood, low SES is not associated with the "core" symptoms of inattention and hyperactivity. Although SES had negative influences on inattentiveness (i.e., low SES was predictive of higher levels of inattentiveness) and had positive effects on students' attitudes toward reading, reading activity at home and reading achievement, the effects were mostly small and insignificant. However, the direct effects of inattentiveness on reading achievement were significant and negative, as they were on students' attitudes toward reading and reading activity at home. Furthermore, the magnitudes of the direct effects of reading activity at home on achievement (mediated by the indirect effects of attitudes on achievement) actually increased with student age, suggesting the importance of reading at home as a major influencing variable affecting student achievement (Rowe, 1991). Second, consistent with the view expressed by McGee and Share (1988), namely, " ... that a substantial overlap exists between ADDH and learning difficulties ..." (p. 322), for learning disabled groups, the present findings related to the magnitude of the reciprocal effects between inattentiveness and reading achievement in a normal school population 'indicated that the effects were strongly interdependent for all student age groups. However, the view that " ... most ADDH is a consequence of learning difficulties at school rather than the reverse" (McGee and Share, 1988, p. 322), may require some qualification. The evidence reported here supports the first two Rutter et al. (1970) hypotheses cited in Part A, namely: 1) problem behavior leads to reading difficulties, and 2) reading difficulties lead to behavior problems. That is, for the sample of students in the present study, inattentive behaviors in the classroom had strong negative influences on their reading achievement, and lower levels of reading achievement led to increases J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

in inattentiveness. Alternatively, higher levels of reading achievement, mediated by the positive effects of reading activity at home and related attitudes toward reading, had significant influences on reducing the impact of inattentive behaviors (i.e., increasing attentiveness). Third, results from this study have provided strong support for the claimed benefits of Reading Activity at Home and the related value recognizing the important contributions that parents can (and many do) make to the educational development of their children (Hewison, 1988; Kirner, 1989; Rowe, 1991; Topping and Wolfendale, 1985; Winter, 1988). For students in the 5- to 6-year-old group, high scores on the shared reading items in particular, had strong positive effects on attitudes toward reading and on reading achievement. Moreover, for all age groups, high scores on the reading alone item (READ 1) had significant influences on reading achievement, which, in tum, contributed strongly toward reducing the negative impact of inattentive behaviors in the classroom. The implications of the present findings are clear. In view of the salience of the reciprocal relationship between inattentiveness and reading achievement, at least two directions for appropriate classroom management, intervention, and treatment are suggested. First, given the mutuality of learning outcomes and behavior, there is a clear need to focus intervention strategies in both domains simultaneously. Although findings from several studies show positive longterm effects of remediation programs on literacy skills (e.g., Bradley & Bryant, 1983; Limbrick et al. 1985), there is little evidence for long-term gains on behavioral outcomes by remediation of learning difficulties alone. (A possible exception is the work of Arnold et aI., 1977, 1981). On the basis of findings from a recent study among hyperactive and learning-disabled boys, Merrell (1990) notes: "Perhaps concurrent academic and behavioral intervention would be useful in helping many of these students" (p. 294). Secondly, there is a clear need to enhance the positive 365

ROWE AND ROWE

mediating effects of home inputs on students' attitudes, achievement and behavior in the classroom. Because the effects of either direct or indirect parental involvement in students' educational progress are clearly important, it is imperative that the work of schools be supported by programs designed to assist parents to take an active role in the development of their child's reading skills. Cox (1987) argues that' 'school-based measures to prevent early reading failure should be coupled with an early intervention programme designed to encourage and assist parents, where necessary, to take a more active role ..." (p. 84). Consistent with the work of McGee et aI. (1988), findings from this study suggest, however, that parental literacy is likely to have a significant impact on the development of such skills. In this context, government policy has a major role to play. The recent "Reading Together" policy initiative of the Victorian government, (Kirner, 1989), is a major step in this direction. Moreover, programs of the type that provide opportunities through which both parent and child literacy are enhanced would appear to have particular merit (e.g., Hewison, 1988; Limbrick et aI., 1985; Morgan and Lyon, 1979; Tizard et aI. 1982; Topping and Wolfendale, 1985). One participating school in the present study has instituted a program that encourages students at year levels 7 to 9 to read one-act plays at home with their family members in an attempt to enhance both student and family literacy. Anecdotal reports from parents, teachers, and stu-

1>

1--.1 x

1

ENJOY

dents of the effectiveness this program to date are most positive. Finally, within the limitations of fitting cross-sectional models to cross-sectional data referred to above, a major contribution of this study has been the adoption of a methodology for examining putative' 'effect" relationships among factors intrinsic to student-home-school interactions. The methodology employed here has been able to test both the direction and magnitude of effects between Inattentiveness and reading Achievement (including their reciprocal effects), mediated by students' Attitudes toward reading and Reading Activity at Home. As indicated in the companion paper (Part A), much of the related research has been severely limited by the use of methodologies that fail to explicitly account for measurement error in either the observed or latent variables and that fail to specify the direction of effects. The use of structural equation modeling of the kind employed here enables researchers to actually test substantive theories and provide evidence central to the formulation of appropriate educational and clinical intervention strategies. Despite the logistic difficulties involved, additional research of the kind reported here would benefit much from a longitudinal design. Such an approach would provide an opportunity to examine the stability of effects over time and provide a more sure basis for the identification of specific cause and effect relationships.

~ "(.21

02-.jx 2 USEFUL" "( 22

1>3-+jx 3

WELL

~"(i3

TEST SCORE

PROFILE SCORE

Y5

Y6

FIG. 4. Nonrecursive structural equation model.

366

J. Am. Acad. Child Adolesc. Psychiatry, 31:2, March 1992

INATTENTIVENESS AND READING ACHIEVEMENT (PART B)

Appendix

Structural Equations for the Recursive Model (Modell)

For these analyses, the LISREL method for Submodel 3b was used (Joreskog and Sorbom, 1989b, pp. 189-190). This general model contains only y (observed) and 11 (latent) variables. In matrix notation, the structural relationships among the latent variables (11) are given by: 11

=

Bll +

S,

where the measurement model for the y variables is given by

y = A/I - B)'I S + E, and the covariance matrix of y is L = A/I - B)'I\}l(I - B')'lAy'

+ 8E.

This model has only four parameter matrices-namely, A y , B, X, and 8E, where A y is the matrix of factor loadings for the y variables, B is the matrix of directional relationships among the latent endogenous constructs (11), X is the matrix of covariances and variances among the residuals of the endogenous constructs, and 8E is the matrix of error variances and covariances among the y variables. The major interest in this study concerned the estimation of the directional parameters of B. Structural Equations for the Nonrecursive Model (Model 2) For these analyses, the LISREL nonrecursive method for path analysis with latent variables was used (Joreskog and Sorbom, 1989b, pp. 177-188). The structural relations among the latent variables is given by: 11

=

Bll + rx +

S,

and the measurement model for the y variables is given by y = Ayll + E. References ACER (1979), Primary Reading Survey Test, Level AA - Word Recognition. Hawthorn, Vic: The Australian Council for Educational Research. Arnold, L. E., Barnebey, N., McManus, J, et al. (1977), Prevention by specific perceptual remediation for vulnerable first-graders. Arch. Gen. Psychiatry, 24:1279-1294. - - Smelzer, D. J. & Barnebey, N. S. (1981), Specific perceptual remediation. Psycho!. Rep., 49:198. Berry, W. D. (1984). Non-recursive Causal Models. Sage University Paper Series on Quantitative Applications in the Social Sciences, series no. 07-037. Beverly Hills and London: Sage Publications. Bradley, L. & Bryant, P. E. (1983), Categorizing sounds and learning to read: a causal connection. Nature, 301 :419-421. Brown, R. L. (1989), Using covariance modeling for estimating reliability on scales with ordered polytomous variables. Educational and Psychological Measurement, 49:383-398. Calfee, R. & Drum, P. (1986), Research on teaching reading. In: Handbook of research on teaching, ed. M. C. Wittrock. 3rd ed. New York: Macmillan, pp. 804-849. Castles, I. (1986), Australian Standard Classification ofOccupations: Statistical Classifications, Australian Bureau of Statistics. Canberra: C. J. Thompson Government Printer. Cox, T. (1987), Slow starters versus long-term backward readers. Br. J. Educ. Psychol., 57:73-86.

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Crano, W. D. & Mendoza, J. L. (1987), Maternal factors that influence children's positive behavior: demonstration of a structural equation analysis of selected data from the Berkeley Growth Study. Child Dev., 58:38-48. Gollob, H. F. & Reichardt, C. S. (1987), Taking account of time lags in causal models. Child Dev., 58:80--92. Griffin, P. E. (1990), Profiling literacy development: monitoring the accumulation of reading skills. Australian Journal of Education, 34:290--311. - - & Nix, P. (1991), Educational Assessment and Reporting: A New Approach. London: Harcourt Brace Jovanovich. Hewison, J. (1988), The long term effectiveness of parental involvement in reading: a follow-up to the Haringey Reading Project. Br. J. Educ. Psycho!., 58:184-190. Joreskog, K. G. (1971), Statistical analysis of sets of congeneric tests. Psychometrika, 36: 109-133. - - Sorbom, D. (1988), PRELlS: A Program for Multivariate Data Screening and Data Summarization: A Preprocessor for LlSREL, 2nd ed. Mooresville, IN: Scientific Software, Inc. - - Sorbom, D. (1989a), LlSREL 7: A Guide to the Program and Applications. Chicago: SPSS, Inc. - - Sorbom, D. (1989b), LlSREL 7 User's Reference Guide. Mooresville, IN: Scientific Software, Inc. Kirner, J. (1989), An open letter from the Minister for Education. In Victoria 1989, Reading together: a major initiative for literacy prep-year 3 from the Ministry of Education. Melbourne: Jean Gordon Government Printer. Kysel, F., Varlaam, A., Stoll, L. & Sammons, P. (1983), The Child at School: A New Behaviour Schedule. Internal Report RS 907/83. London: Inner London Education Authority, Research and Statistics Branch. Limbrick, E., McNaughton, S. & Glynn, T. (1985), Reading gains for underachieving tutors and tutees in a cross-age tutoring programme. J. Child Psycho!. Psychiatry, 26:939-953. Loney, J. & Milich, R. (1982), Hyperactivity, inattention and aggression in clinical practice. Advances in Developmental and Behavioral Pediatrics, 3:113-147. McGee, R. & Share, D. L. (1988), Attention deficit disorder-hyperactivity and academic failure: which comes first and what should be treated? J. Am. Acad. Child Adoles. Psychiatry, 27:318-325. - - Williams, S. & Silva, P. A. (1987), A comparison of boys and girls with teacher-identified problems of inattention. J. Am. Acad. Child Adolesc. Psychiatry, 26:711-717. - - - - - - (1988), Slow starters and long-term backward readers: a replication and extension. Br. J. Educ. Psycho!., 58:330--337. McKinney, J. D. (1989), Longitudinal research on the behavioral characteristics of childen with learning disabilities. Journal of Learning Disabilities, 22:141-150. Merrell, K. W. (1990), Teacher ratings of hyperactivity and selfcontrol in learning-disabled boys: a comparison with low-achieving and average peers. Psychology in the Schools, 27:289-296. Morgan, R. & Lyon, E. (1979), 'Paired Reading'-a preliminary report on a technique for parental tuition of reading-retarded children. J. Child Psycho!. Psychiatry, 20:151-160. Mossenson, L., Hill, P. & Masters, G. (1987), Tests ofReading Comprehension (TORCH): Manua!. Hawthorn, VIC: Australian Council for Educational Research. Pedhazur, E. J. (1982), Multiple Regression in Behavioral Research: Explanation and Prediction, 2nd ed. New York: Holt, Rinehart and Winston. Rowe, K. J. (1989), The commensurability of the general linear model in the context of educational and psychosocial research. Australian Journal of Education, 33:41-52. - - (1991), The influence of reading activity at home on students' attitudes towards reading, classroom attentiveness and reading achievement: an application of structural equation modeling. Br. J. Educ. Psycho!., 61:19-35. - - Griffin, P. E. (1988), Literacy Programs in Victorian Schools: Proposal for a Longitudinal Study, Melbourne, VIC: Ministry of Education, Schools Division. - - Rowe, K. S. (1989), Assessing Behavioural Change: The Development and Psychometric Properties of a Parent and Teacher-

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administered Child Behaviour Inventory for Use in Educational and Epidemilogical Research. Melbourne, VIe: School Programs Division, Ministry of Education (Victoria), and Department of Paediatrics, The University of Melbourne. - - Sykes, J. (1989), The impact of professional development on teachers' self perceptions. Teaching and Teacher Education, 5:129-141. Rutter, M. (1985), Family and school influences on behavioural development. J. Child PsychoI. Psychiatry, 26:349-368. --Tizard, J. & Whitmore, K. (1970), Education, Health and Behaviour. London: Longmans. Share, D. L., Jorm, A. F., Maclean, R., Matthews, R. & Waterman,

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B. (1983), Early reading achievement, oral language ability and a child's home background. Australian Psychologist, 18:75-87. Tizard, J., Schofield, W. & Hewison, J. (1982), Collaboration between teachers and parents in assisting children's reading. Br. 1. Educ. Psychol., 52:1-15. Topping, K. & Wolfendale, S. (Eds.) (1985), Parental Involvement in Children's Reading. Beckenham: Croom Helm. Walberg, H. J. & Tsai, S. (1985), Correlates of reading achievement and attitude: a national assessment study. Journal of Educational Research, 78:159-167. Winter, S. (1988), Paired reading: a study of process and outcome. Educational Psychology, 8:135-151.

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