ASSESSMENT OF CHILDREN’S BEHAVIOR BEFORE AND AFTER …

ASSESSMENT OF CHILDREN’S BEHAVIOR BEFORE AND AFTER MASS DRUG

ADMINISTRATION WITH PRAZIQUANTEL IN KENYA USING BASC-2

by

XIANJUE WEI

(Under the Direction of Ye Shen)

ABSTRACT

Schistosomiasis is an underreported infection that can cause anemia, decreased growth,

liver abnormalities, and deficits in cognitive functioning to children. This study used Behavior

Assessment System for Children (BASC-2) to collect the raw data of children’s behaviors with

or without schistosomiasis in Kenya before and after mass drug administration (MDA) with

praziquantel. We performed multiple imputation to deal with the missing data, and applied

several statistical procedures such as paired t-test and linear mixed effect models to investigate

the impact of schistosomiasis infection on children’s behavior and whether the MDA leads to

positive effects on children’s behaviors. The results of this study generally supported our

expectation that children have better behaviors without schistosomiasis, and children’s

behaviors, especially problematic behaviors, will improve significantly after the praziquantel

treatment.

INDEX WORDS: BASC-2, Children Behavior, Schistosomiasis, Mass Drug Administration,

Statistical Analysis



by

XIANJUE WEI

B.A., Beijing Jiaotong University, China, 2014

A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment

of the Requirements for the Degree

MASTER OF SCIENCE

ATHENS, GEORGIA

2016

© 2016

XIANJUE WEI

All Rights Reserved



by

XIANJUE WEI

Major Professor: Ye Shen

Committee: Stephen L. Rathbun

Xiao Song

Electronic Version Approved:

Suzanne Barbour

Dean of the Graduate School

The University of Georgia

May 2016

iv

ACKNOWLEDGEMENTS

I appreciate the advice from Dr. Shen, Dr. Rathbun, Dr. Song, and all the other professors

who taught and helped me. I thank my parents who supported me to have the opportunity to

study in the U.S. and made my American dream come true.

v

TABLE OF CONTENTS

Page

ACKNOWLEDGEMENTS ........................................................................................................... iv

LIST OF TABLES ......................................................................................................................... vi

LIST OF FIGURES ..................................................................................................................... viii

CHAPTER

1 INTRODUCTION .........................................................................................................1

Purpose of Study ......................................................................................................1

Research Question and Hypotheses .........................................................................3

2 MATERIAL AND METHODS .....................................................................................4

Data Collection ........................................................................................................4

BASC-2 ....................................................................................................................5

Multiple Imputation ...............................................................................................10

Statistical Analysis .................................................................................................11

3 RESULTS AND DISCUSSION ..................................................................................16

Results ....................................................................................................................16

Discussion ..............................................................................................................35

4 CONCLUSION ............................................................................................................40

REFERENCES ..............................................................................................................................41

APPENDICES

A MULTIPLE IMPUTATION RESULTS......................................................................44

vi

LIST OF TABLES

Page

Table 1: TRS Scale Definition .........................................................................................................7

Table 2: Example of the Composite T Scores Summary of One Child ...........................................8

Table 3: Factor Correlation from CSA for TRS-C ..........................................................................9

Table 4: Scale and Composite Score Classification ......................................................................12

Table 5: Frequency of the Classification of Children’s Behaviors before Treatment ...................17

Table 6: Mean Composite T Scores before Treatment ..................................................................17

Table 7: Frequency of the Classification of Children’s Behaviors after Treatment ......................19

Table 8: Mean Composite T Scores after Treatment .....................................................................19

Table 9: Mean Scores of Subscales of Externalizing Problems ....................................................20

Table 10: Mean Scores of Subscales of Internalizing Problems....................................................22

Table 11: Mean Scores of Subscales of School Problems .............................................................22

Table 12: Mean Scores of Subscales of Adaptive Skills ...............................................................23

Table 13: Paired T-test: Before-treatment vs After-treatment .......................................................26

Table 14: MANOVA Test and Exact F statistics...........................................................................27

Table 15: Simultaneous and Bonferroni Confidence Interval .......................................................27

Table 16: MANOVA Test and Exact F statistics for Parallel Profiles ..........................................28

Table 17: Paired T-test for Adaptive Scales: Before-treatment vs After-treatment ......................29

Table 18: P-values of Type 3 Tests of Fixed Effect ......................................................................31

Table 19: Solution for Fixed Effects of Externalizing Problems ...................................................32

vii

Table 20: Solution for Fixed Effects of Internalizing Problems ....................................................32

Table 21: Solution for Fixed Effects of School Problems .............................................................33

Table 22: Solution for Fixed Effects of BSI ..................................................................................33

Table 23: Solution for Fixed Effects of Adaptive Skills ................................................................33

Table 24: Mean Changes Following MDA

between Positive and Negative Groups ..........................................................................34

Table 25: McNemar’s Test for F Index .........................................................................................35

Table 26: McNemar’s Test for Consistency Index ........................................................................35

viii

LIST OF FIGURES

Page

Figure 1: Mean Composite T Scores before Treatment .................................................................18

Figure 2: Mean Composite T Scores after Treatment ....................................................................19

Figure 3: Mean Composite T Scores by Status and Time .............................................................20

Figure 4: QQ Plots by Time ...........................................................................................................24

Figure 5: QQ Plots by Status .........................................................................................................25

Figure 6: Profile Plot of Composite Scales: Before-treatment vs After-treatment ........................28

Figure 7: Spaghetti Plots for Externalizing Problems, Internalizing Problems, BSI, School

Problems and Adaptive Skills ........................................................................................30

Figure 8: Mean Changes Following MDA

between Positive and Negative Groups ..........................................................................34

1

CHAPTER 1

INTRODUCTION

Purpose of Study

This study seeks to test the difference in behaviors between school children with and

without schistosomiasis who underwent the mass drug administration (MDA) of praziquantel in

Kenya using the Behavior Assessment System for Children 2nd Edition (BASC-2).

Schistosomiasis is an acute and chronic parasitic disease caused by blood flukes

(trematode worms) of the genus Schistosoma. The World Health Organization (WHO) states that

more than 61.6 million people were reported to have been treated for schistosomiasis in 2014,

and at least 258 million people were estimated to be in need of preventive treatment for

schistosomiasis in 2014 [1]. In comparison to diseases with high mortality such as human

immunodeficiency virus (HIV) and malaria, schistosomiasis exists at the morbidity level and has

been historically underreported [2].

Schistosomiasis is prevalent in tropical and subtropical areas, especially in poor

communities [1], and is concentrated in sub-Saharan Africa [3]. The prevalence of

schistosomiasis is very high in western Kenya, with some areas reporting prevalences as high as

65% [4].

As prevention of exposure to the parasite is challenging in areas where the disease is

endemic, the main approach to preventing morbidity from schistosomiasis is to treat people

annually with praziquantel, usually through Mass Drug Administration (MDA). MDA is the

treatment of the entire population in a geographic area with a curative dose of a drug without

2

first testing for infection and regardless of the presence of symptoms [5]. Since 2003, MDA

using praziquantel was implemented to reach children in primary schools located in areas where

the disease is endemic for schistosomiasis, and all children are treated irrespective of their

infection status [6]. In children, schistosomiasis typically presents with generalized, non-specific

signs and symptoms, making it difficult to identify disease-specific morbidity indicators and

challenging to develop tools for assessing those indicators [3]. In school-aged children, infection

can cause anemia, decreased growth, liver abnormalities, and deficits in cognitive functioning.

Therefore, it is important to prevent schistosomiasis infection in children.

Most previous studies [2-5] about schistosomiasis in children focused on subtle morbidity

including anemia, debilitating, stunted growth, impaired cognitive development, etc., before and

after the treatment. Very few studies investigated children’s behaviors that are vital for their

healthy development of children. In this study, we propose to assess children’s behavior before

and after mass drug administration with praziquantel in Kenya using the BASC-2 tool.

BASC-2 is the second edition of the behavior assessment system for children. It is a

norm-referenced diagnostic tool designed to assess the behavior and self-perceptions of children

and young adults aged 2 through 25 years [7]. It was designed to facilitate the differential

diagnosis and educational classification of a variety of emotional and behavioral disorders of

children and to aid in the design of treatment plans [8]. It typically asks respondents to report

how often a child displays various behaviors, leaving it to them to judge how situational factors

should be taken into account [9]. Teachers rate the presence of behaviors in children on a four-

point frequency scale (i.e., 1=Never, 2=Sometimes, 3=Often, and 4=Almost Always). Raw item

scores are summed and converted by BASC-2 software into T scores for easy comparison. Since

its publication in 1992, the BASC has become one of the most widely used tools for assessing

3

behavior and emotions in children, adolescents, and young adults [10]. For this study, the BASC-

2 can be very useful for reporting the children’s behaviors and comparing scores across time and

by schistosomiasis status.

To our knowledge, there is no previous study in which the BASC-2 was used to collect

raw data and generate reports about children’s behaviors to detect the differences in children

with and without schistosomiasis, and to evaluate the changes in children’s behaviors before and

after the treatment with praziquantel. Scientific advances in the field calls for the study of the

impact of MDA on behaviors among school-age children using BASC-2 for a better

understanding of the current practices in treating schistosomiasis in Sub-Saharan Africa.

Research Question and Hypotheses

The purpose of the current study is to examine the impact of mass drug administration on

children’s behaviors for those with negative or positive schistosomiasis status by using the

BASC-2 Teacher Rating Scales. Specifically, this research addressed the following questions:

1. Is there a significant change in composite T scores in children after the mass drug

administration of praziquantel?

2. Do school-age children with positive schistosomiasis status have significantly

different scores on the composite scales of the BASC-2 TRS compared to children

with negative status?

3. Is there a greater change in the composite T scores following treatment among

children with positive status compared with those with negative status?

4

CHAPTER 2

MATERIAL AND METHODS

Data Collection

All the data used in this study were collected in Kenya by the U.S. Centers for Disease

Control and the Kenya Medical Research Institute. Six teachers of classes containing children

ages 8-11 years were asked to participate. These teachers were from villages where the 2014

prevalence of schistosomiasis was high and there were at least 15 children with ≥400 eggs/gram

feces using standard diagnostic tests. The class teachers were recruited to help in this study since

they spend more time with the pupils compared to others and were, therefore, in a better position

to offer insights into the pupils’ behaviors.

Prevalence surveys were conducted as usual in January 2015. A total of 36 children from

six different schools were selected for this study. Six children were selected from each school

with a participating teacher: Three children were randomly selected from children with no eggs

in their stools (negative infection status), and three were randomly selected from among those

with at least 400 eggs per gram feces (positive infection status). Parental consent and child assent

were obtained at enrollment. The teacher and investigator were blinded as to which of the

children were infected and which had no eggs in stool.

After training by the research team, teachers used the BASC-2 questionnaires forms to

evaluate the children on days prior to initiation of MDA to collect the before-treatment data.

MDA occurred in February 2015, and following MDA, the teachers evaluated the same children

5

using the BASC-2 to collect the after-treatment data. Changes in scoring between the two time

points were evaluated.

In this study, there are 36 children with a mean age of 9.9 years, with half of them (n=18)

being schistosomiasis positive, and the other half being negative based on the stool results. The

information of each child was collected twice before- and after-treatment, with the expectation

on a full dataset of 72 observations. However, there was one child from whom only before-

treatment data was recorded. Hence, 71 observations were included in the complete-case analysis

and multiple imputation approach was used to serve as a sensitivity check in the following

analysis. Together, there are 29 variables for each observation: name, id, time (before or after),

age, status (negative or positive), school, F Index, Consistency Index, Response Pattern Index,

Externalizing Problems, Internalizing Problems, School Problems, Behavioral System Index

(BSI), Adaptive Skills, Hyperactivity, Aggression, Conduct Problems, Anxiety, Depression,

Somatization, Attention Problems, Learning Problems, Atypicality, Withdrawal, Adaptability,

Social Skills, Leadership, Study Skills, and Functional Communication. The schistosomiasis

status in this study is only from the tests carried out before the treatment.

BASC-2

The Behavior Assessment System for Children (2nd edition; BASC-2) is the most widely

adopted broad-based behavioral rating scale used by school-based practitioners [6].

BASC-2 norms are based on large, representative samples and are differentiated

according to the age, sex, and clinical status of the child. There are two norms which can be

chosen to derive standard scores for the various subscales and composite: sex-based norms and

combined-sex norms [8]. The norm sample we used in this study is the general combined-sex

norm.

6

There are three types of scales in BASC-2: Teacher Rating Scales (TRS), Parent Rating

Scales (PRS), and Self-Report of Personality (SRP) [8]. In this study, we applied the TRS to

evaluate children’s school behaviors.

The TRS is a comprehensive measure of both adaptive and problematic behaviors in the

school setting. It has three forms, with items targeted at three age levels: preschool (2 through 5),

child (6 through 11), and adolescent (12 through 21) [8]. For our study, TRS-C was used, as the

ages of the enrolled students (8-11) fall into the “child” group. The TRS has between 100 and

139 items rated on a 4-point scale of behavioral frequency from “Never” to “Almost Always”.

Our working dataset has information on 129 of these items. Teachers respond to these items with

Never, Sometimes, Often, or Almost Always, respectively corresponding to the score in the

BASC-2 software of 1, 2, 3, and 4.

The BASC-TRS yields 5 composite scales, 10 clinical scales, and 5 adaptive scales. The

broad composite scales are Externalizing Problems, Internalizing Problems, School Problems,

Adaptive Skills and the Behavioral System Index (BSI). The Externalizing Problems contains

Hyperactivity, Aggression, and Conduct problems, which are disruptive in nature. The

Internalizing Problems indicates not acting-out behaviors, including Anxiety, Depression,

Somatization, Atypicality, and Withdrawal. The School Problems reflecting academic difficulties

contains Attention Problems, and Learning Problems. The Adaptive Skills is the core

characteristics of adaptive behaviors, which has five subscales: Adaptability, Functional

Communication, Social Skills, Leadership, and Study Skills. The BSI contains Hyperactivity,

Aggression, Depression, Atypicality, Withdrawal, and Attention problems, and it assesses the

overall level of problem behaviors [8]. Table 1 presents the definition of each individual scale.

7

Table 1 TRS Scale Definition

Category Composite scale Scale Definition

Clinical

scales

Externalizing

Problems

Hyperactivity The tendency to be overly active, rush

through work or activities, and act without

thinking

Aggression The tendency to act in a hostile manner

(either verbal or physical) that is

threatening to others

Conduct Problems The tendency to engage in antisocial and

rule-breaking behavior, including

destroying property

Internalizing

Problems

Anxiety The tendency to be nervous, fearful, or

worried about real and imagined problems

Depression Feelings of unhappiness, sadness, and

stress that may result in an inability to

carry out everyday activities or may bring

on thoughts of suicide

Somatization The tendency to be overly sensitive to and

complain about relatively minor physical

problems and discomforts

Atypicality The tendency to behave in ways that are

considered “odd” or commonly associated

with psychosis

Withdrawal The tendency to evade others to avoid

social contact

School Problems Attention Problems The tendency to be easily distracted and

unable to concentrate more than

momentarily

Learning Problems The presence of academic difficulties,

particularly understanding or completing

homework

Adaptive

scales

Adaptive Skills Adaptability The ability to adapt readily to changes in

the environment

Functional

Communication

The ability to express ideas and

communicate in a way others can easily

understand

Social Skills The skills necessary for interacting

successfully with peers and adults in home,

school, and community settings

Leadership The skills associated with accomplishing

academic, social or community goals,

including the ability to work with others

Study Skills The skills that are conducive to strong

academic performance, including

organizational skills and good study habits

8

The individual scales in Externalizing Problems, Internalizing Problems, School

Problems and the BSI are all clinical scales, which measure maladaptive behaviors, and high

scores for these behaviors indicate problematic levels. The scales in Adaptive Skills are adaptive

scales, which measure positive behaviors, and low scores indicate problematic levels. Table 2 is

an example of the report on the composite T scores BASC-2 created for one child. T scores

indicate the distance of scores from the norm-group mean, with a mean of 50 and a standard

deviation of 10. The BASC-2 T scores are not normalized; they are linear transformations of

raw-scores [8].

Table 2 Example of the Composite T Score Summary of One Child

Raw

score T score

Percentile

rank

95% confidence

interval

Externalizing Problems 139 46 41 43-49

Internalizing Problems 195 69 95 63-75

School Problems 80 39 12 34-44

Behavioral Symptoms

Index 296 49 55 46-52

Adaptive Skills 273 55 60 52-58

To ensure reliability of the scales, BASC-2 employs the factor analysis to generate the

composite T scales. Factor analysis is the statistical technique used in identifying TRS

composites which assess broad dimensions. In BASC-2, each item is placed on one factor

(scale), and all factors are allowed to be correlated [8]. Two types of factor analyses were

performed. The primary technique was covariance structure analysis (CSA). The CSA was used

to evaluate the model and modify it in an appropriate way according to the results of the analysis.

Table 3 is an example of CSA factors that provide information on construct validity of the

composites and scales. From Table 3, the Externalizing Problems factor assesses a behavior

dimension that is common to the content of the Hyperactivity, Aggression and Conduct Problem

9

[8], since they have a high level of intercorrelation. For Internalizing Problems, Depression,

Atypicality, and Withdrawal contribute more to this factor, while Anxiety and Somatization are

less informed by this factor. The School Problems factor has high correlations with both

Attention Problems and Learning Problems scales [8]. Finally, the Adaptive Skills factor has

very high intercorrelations for all the subscales except Adaptability. The second type of factor

analysis is the principal-axis analysis, which is a purely exploratory method used to see whether

factor-structure models other than those evaluated with CSA could provide a good fit to the scale

intercorrelation data [8]. Since the principal-axis method may reveal a substantially different

factor structure not indicated by CSA, it is considered to be a complement of CSA.

Table 3 Example of Factor Correlation from CSA for TRS-C

TRS-C

Scale Externalizing

Problems

Internalizing

Problems

School

Problems

Adaptive

Skills

Hyperactivity 0.89

Aggression 0.90

Conduct Problems 0.91

Anxiety 0.51

Depression 0.85

Somatization 0.41

Atypicality 0.75

Withdrawal 0.80

Attention Problems 0.91

Learning Problems 0.74

Adaptability 0.39 Functional

Communication 0.86

Social Skills 0.81

Leadership 0.91

Study Skills 0.90

To measure the validity of children’s responses, there are three indexes: F index,

Consistency index, and Response Pattern Index. The F-index score is a tally of the number of

times the respondent provides a very negative behavior rating [8]. The Response Pattern Index is

10

designed to identify forms that may be invalid due to that fact that the respondents are inattentive

to the item content [8]. The Consistency Index identifies cases in which the respondent offer

inconsistent answers to items that usually are answered similarly [8]. If the responses are

consistent, the value of Consistency Index is “acceptable”; otherwise, the Consistency Index is

“caution”. The Response Pattern index is acceptable for all the observations in our study, so we

only conducted further analysis on the F Index and Consistency Index.

In our analysis, the BASC-2 software was used to preprocess the raw data collected from

the BASC-2 TRS-C questionnaires to generate T scores, which were then entered into a working

dataset for further exploration.

Multiple Imputation

Since there are missing data in our study, we attempted to handle it statistically as a

sensitivity check. There are several popular existing practices for handling missing data. Most

procedures in SAS use the Complete-Case Analysis (CCA) by default to deal with missing data.

The approach we adopted, so-called multiple imputation (MI), often assumes that missing values

are missing at random (MAR) in which the probability that a datum is missing may depend on

observed characteristics but not on unobserved characteristics of the subject [11]. Multiple

imputation can provide unbiased statistical results given a correctly specified imputation model

[12].

There are various imputation approaches available for multiple imputation. In our

analysis, considering that we have both continuous and categorical variables to be imputed and

that an arbitrary missing data pattern allows more flexibility over a monotone missing pattern,

we applied the fully conditional specification (FCS) approach, which is based on a flexible

11

selection of univariate imputation distributions without ever formally specifying the joint

multivariate density [13].

There are three steps to dealing with missing data in multiple imputation: the first step is

to introduce random variation into the imputation process and generate several data sets, each

with different imputed values; the second step is perform the desired analysis on each data set;

the last step is to combine the results into a single set of parameter estimates, standard errors, and

test statistics. For our study, in the first step, direct replacement of subjects was done by new

subjects from an identifiable source population based on observed subject characteristics [12],

and the number of imputation datasets we created was 10 (default in SAS 9.4 is 5). In the second

step, each imputed data set again was analyzed using the standard analytical techniques

(calculating means, t test, and longitudinal analysis in this study). And in the third step, “proc

mianalyze” was used to combine the results from the 10 complete data sets. All the results of

multiple-imputation are presented in the Appendices A as a sensitivity check reference to the

primary analysis results from CCA shown in the main text.

Statistical Analysis

In the preprocessing stage for the raw data, the numerical values on a four-point scale (1,

2, 3, and 4) of the question items were entered into the BASC-2 software manually. The BASC-2

software then generated reports for each child and exported them as electronic documents. After

that, the derived T scores for the BASC TRS domains were entered into an Excel spread-sheet

with 71 observations and 29 variables, and it was later converted to a sas7bdat file for further

analysis.

The working dataset was analyzed using SAS version 9.4 (SAS Institute Inc., Cary, NC)

[14]. All tests and confidence intervals used the 5% level of significance.

12

Descriptive statistics were obtained to check the baseline information about children’s

behaviors before mass drug administration. Composite T scores were classified into three ranges

and a frequency table was given. In BASC-2, the scale and composite score classification is

shown in Table 4. We combined average, high and very high (average, low and very low) ranges

together in this analysis, since the three classes represent good behaviors. At-Risk range may

signify potential or developing problems that need to be monitored carefully, while the

clinically-significant range denotes a high level of maladaptive behaviors [8]. The mean scores

of Externalizing Problems, Internalizing Problems, School Problems, Adaptive Skills and the

Behavioral System Index (BSI) were calculated by status (Negative or Positive). A histogram

was presented to describe the mean scores of these five composite scales with negative status and

positive status. Then the analysis was repeated to get information about children’s behaviors

after the MDA.

Table 4 Scale and Composite Score Classification

Classification

T-score Range Adaptive Scales Clinical Scales

Very High Clinically Significant 70 and above

High At-Risk 60-69

Average Average 41-59

At-Risk Low 31-40

Clinically Significant Very Low 30 and below

For calculating the mean T scores of these variables by time and status simultaneously,

time and status were categorized into four groups as follows:

A-: After-treatment and negative status (without schistosomiasis)

A+: After-treatment and positive status (with schistosomiasis)

B- : Before-treatment and negative status

B+: Before-treatment and positive status

13

Further descriptive analysis was conducted for the subscales of each composite scale to

explore which subscale contributed more to the composite T scores of each composite scale, and

should consequently draw more attention.

Normality checking for the dataset was done using the QQ plot by time and status

respectively, to ensure that methods relying on normal distributional assumptions are valid.

To test the first hypothesis on whether there is a significant difference in the composite T

scores between before-treatment and after-treatment, a paired two-sample t-test was conducted.

The paired sample t-test typically consists of a sample of matched pairs of similar units, or one

group of units that has been tested twice, as was the case in our BASC-2 evaluated T scores. In

addition, we also considered the paired two sample Hotelling’s T2 test of multivariate scales as a

supplementary method to test the differences in composite T scales with an adjustment for

multiple comparisons [15]. A profile analysis was conducred as part of the Hotelling’s T2 test,

and confidence intervals were obtained. By using the profile analysis, we can visually compare

the change of mean scores in each composite scale across the before-treatment group and after-

treatment group.

Spaghetti plots were presented by positive and negative group respectively for

Externalizing Problems, Internalizing Problems, School Problems, Adaptive Skills and the

Behavioral System Index (BSI) to explore the difference in trajectories of child’s behaviors

following the MDA.

To test the second hypothesis on whether there is a significant difference between the

schistosomiasis negative and positive groups, multi-level linear mixed effects models were built

for each composite scale. Linear mixed effects models are particularly useful in settings where

repeated measurements are made on the same statistical units (longitudinal study), or where

14

measurements are made on clusters of related statistical units. Longitudinal studies can be very

powerful, both statistically and scientifically, because they enable one to study changes within

individual subjects over time or under varied conditions [16]. To account for correlated outcome

measures, linear mixed effects models estimate a pooled multi-level equation by simultaneously

incorporating fixed and random effects [17].

The following linear mixed-effects model was considered:

Yijk = β0 + β1 Status + β2Time+ β3 Status*Time + εk + εi(k) + eijk ,

where Yijk represents the mean in composite T score of each composite scale for child i at jth

time of the kth school, β0 is the fixed intercept, β1, β2, and β3 are fixed coefficients of status, time

and the interaction term, eijk ~ N(0, σe2) is the measurement error, εk ~ N(0, σb1

2) is the random

effect at school level, εj(k) ~ N(0, σb22) is the random effect at individual level. For all the fits, we

used usual normal maximum likelihood (ML) with an unstructured covariance model. Several

covariance models had been tried, but the AIC of unstructured covariance model was the

smallest one, so we selected unstructured covariance model in the analysis.

Finally, a subgroup analysis and an independent sample t test were run to test the third

hypothesis: whether the change is greater in composite T scores following treatment among

children with positive status than among those with negative status.

Since the F Index and Consistency Index for some children changed after the treatment,

McNemar’s Tests were conducted to test the difference in F Index and Consistency Index

following MDA. In the BASC-2 software, there are 3 levels of F Index and Consistency Index:

acceptable, caution, extreme caution. In our study, we combined the “caution” and “extreme

caution together as flags for extra attention and created a 2x2 McNemar’s Test table. Here we

chose McNemar’s Test over Chi-square Test due to the fact that our variables are paired.

15

McNemar’s Test does not test for independence, but consistency in response across two variables

[18].

16

CHAPTER 3

RESULTS AND DISCUSSION

Results

Baseline information about children’s behaviors before the mass drug administration,

such as the frequency of the overall range of children’s behaviors (Table 5) and the means of the

composite T scores of the Externalizing Problems, Internalizing Problems, School Problems,

Adaptive Skills and BSI (Table 6) were obtained. From Table 5, more schistosomiasis positive

children are in the at-risk range and the clinically-significant range than schistosomiasis negative

children in all of the five composite scales. In both schistosomiasis status groups, children

behaved the worst on internalizing problems, in which most of them are categorized into the

below-average range, and the best on adaptive skill with none in the clinically-significant range.

From Table 6 and Figure 1, the mean scores of the Externalizing Problems, Internalizing

Problems, School Problems and BSI are larger in the positive group than in the negative group,

suggesting that children with schistosomiasis have more severe problematic behaviors. Among

these composite scales, the difference between negative group (54.61) and positive group (61.72)

is the greatest for the mean score of the Externalizing Problems. The mean scores of

Externalizing Problems, School Problems and BSI from the schistosomiasis positive status group

are in the at-risk range, as compared with those categorized as average from the schistosomiasis

negative status group. Regarding Internalizing Problems, both mean scores exceed the average

range, reaching the at-risk range in the negative group, and the clinically-significant range in the

positive group. For Adaptive Skills, the mean score in the positive group is smaller than that of

17

the negative group, indicating that children in the positive group performed worse on adaptive

scales. However, the difference in the two groups (46.83 vs. 44.83) is relatively small, and both

are in the average range. The standard deviations from all the composite scales except

Internalizing Problems are larger in the positive group, suggesting lower within-group

heterogeneities from the children in the negative group.

Since missing data only occur in the after-treatment measurement, no imputation was

conducted in the baseline analyses.

Table 5 Frequency of the Classification of Children’s Behaviors before Treatment

Status Range Externalizing

Problems

Internalizing

Problems

School

Problems

Behavioral

Symptoms

Index

Adaptive

Skills

Negative Average 13 (72.22%) 3 (16.67%) 11(61.11%) 13 (72.22%) 14 (77.78%)

At-risk 4 (22.22%) 8 (44.44%) 7 (38.89%) 3 (16.67%) 4 (22.22%)

Clinically

significant 1 (5.56%) 7 (38.89%) 0 (0.00%) 2 (11.11%) 0 (0.00%)

Positive Average 9 (50.00%) 3 (16.67%) 9 (50.00%) 8 (44.44%) 10 (55.56%)

At-risk 3 (16.67%) 4 (22.22%) 6 (33.33%) 5 (27.78%) 8 (44.44%)

Clinically

significant 6 (33.33%) 11 (61.11%) 3 (16.67%) 5 (27.78%) 0 (0.00%)

Table 6 Mean Composite T Scores before Treatment

Status

Mean (Std Dev)

Externalizing

Problems

Internalizing

Problems

School

Problems

Behavioral

Symptoms Index

Adaptive

Skills

Negative 54.61 (8.17) 68.44 (13.32) 54.72 (8.65) 55.39 (8.57) 46.83 (6.91)

Positive 61.72 (11.74) 70.83 (11.25) 57.06 (12.26) 61.39 (11.42) 44.83 (8.90)

18

Figure 1 Mean Composite T Scores before Treatment

Similar analyses as conducted at baselined were repeated for the after-treatment

measures. After the mass drug administration, in the negative group, we observed no children in

the clinically-significant range in the Externalizing Problems, School Problems, BSI and

Adaptive Skills, and very few in the at-risk range (Table 7). For Internalizing Problems, yet more

children are in the non-average range, with minimal difference between the two groups with

different infection status. Compared to before-treatment (Table 5), overall children’s behaviors

improved in all the composite scales in both groups, with more children in the average range and

less children in the at-rick and clinically-significant range.

Table 8 and Figure 2 report the results from the after-treatment measures. The mean

scores of all the composite scales are larger in the positive group for clinical scales, while

smaller for adaptive scales. In both groups, except for Internalizing Problems, mean scores are

all in the average range for all composite scales, but mean score of Internalizing Problems spread

out in all three ranges. All of the mean scores are smaller from the after-treatment measures for

clinical scales, and larger for adaptive scales than measures from the before-treatment. The

0

10

20

30

40

50

60

70

80

Externalizing

Problem

Internalizing

Problem

School Problem Behavioral

Symptoms Index

Adaptive Skills

Negative Positive

19

results suggest that children’s problematic and adaptive behaviors were both improved after the

MDA with praziquantel.

A sensitivity check considering missing data with multiple imputation was implemented

and minimal differences were detected (Appendices A. Table 1).

Table 7 Frequency of the Classification of Children’s Behaviors after Treatment

Status Range Externalizing

Problems

Internalizing

Problems

School

Problems

Behavioral

Symptoms

Index

Adaptive

Skills

Negative

Average 16 (88.89%) 7 (38.89%) 18 (100.00%) 14 (77.78%) 15 (83.33%)

At-risk 2 (11.11%0 6 (33.33%) 0 (0.00%) 4 (22.22%) 3 (16.67%)

Clinically

Significant 0 (0.00%) 5 (27.78%) 0 (0.00%) 0 (0.00%) 0 (0.00%)

Positive

Average 11 (64.71%) 5 (29.41%) 13 (76.47%) 10 (58.82%) 12 (70.59%)

At-risk 5 (29.41%) 6 (35.29%) 4 (23.53%) 5 (29.41%) 4 (23.53%0

Clinically

Significant 1 (5.88%) 6 (35.29%) 0 (0.00%) 2 (11.76%) 1 (5.88%)

Table 8 Mean Composite T Scores after Treatment

Status

Mean (Std Dev)

Externalizing

Problems

Internalizing

Problems

School

Problems

Behavioral

Symptoms Index

Adaptive

Skills

Negative 52.22 (4.83) 62.22 (10.69) 49.94 (6.90) 53.94 (6.92) 49.61 (9.06)

Positive 56.71 (7.93) 66.59 (13.25) 51.71 (9.82) 57.47 (9.68) 46.71 (10.04)

Figure 2 Mean Composite T Scores after Treatment

0

10

20

30

40

50

60

70

Externalizing

Problem

Internalizing

Problem


Symptoms Index

Adaptive Skills

Negative Positive

20

Figure 3 Mean Composite T Scores by Status and Time

Further analyses on all the subscales under each composite scale were conducted. From

Table 9, for Externalizing Problems, the mean score of Aggression is the highest. The other two,

Hyperactivity and Conduct Problem, have similar mean scores that are below the composite T

scores of the Externalizing Problems.

The results of multiple imputation (Appendices A. Table 2) suggest that overall

difference in mean scores is negligible, while the change of standard deviation in Conduct

Problem is worth noticing.

Table 9 Mean Scores of Subscales of Externalizing Problems

Composite

Scales Subscales

Mean (Std Dev)

Before MDA After MDA

Positive

Group

Negative

Group

Positive

Group

Negative

Group

Externalizing

problem 61.72 (11.74) 54.61 (8.17) 56.71 (7.93) 52.22 (4.83)

Hyperactivity 59.17 (10.07) 52.78 (6.20) 55.24 (7.51) 51.61 (4.77)

Aggression 64.89 (13.53) 56.44 (12.25) 58.59 (8.02) 54.56 (7.25)

Conduct Problem 58.78 (12.98) 53.50 (7.33) 54.59 (10.33) 50.06 (4.39)

0

10

20

30

40

50

60

70

80

Externalizing

Problem

Internalizing

Problem


Symptoms Index

Adaptive Skills

B- B+ A- A+

21

From Table 10, for Internalizing Problems, Somatization has the highest mean score with

a considerable margin over the other subscales. Almost all the mean scores of these subscales are

at average range in both groups at each time.

After multiple imputation (Appendices A. Table 3), the mean scores of all the subscales

except Atypicality had a negligible increase. All the standard deviations increased, and the

changes in Anxiety, Atypicality, and Withdrawal are large while the others can be neglected.

From Table 11, for School Problems, the mean T score of Learning Problem is larger

than that of Attention Problem, suggesting that children may behave better on Attention

Problem, while both of the mean scores are still in the average range.

Sensitivity checks with multiple imputation (Appendices A. Table 4) showed minimal

differences that are considered to be negligible.

Results on Adaptive Skills are presented in Table 12. Functional Communication has the

smallest mean T score which represents the worst behavior, while Social Scales has the largest

mean T score. All the mean T scores of subscales are in the average range. Consistent with the

previous analysis for the Adaptive Skills, results from subscales further confirmed that most

children’s adaptive behaviors are good.

When the missing data were handled (Appendices A. Table 5), the mean scores of

Adaptability, Functional Communication, and Study Skills had slight increases; the mean score

of Social Skills increased over 1.0, but the mean score of Leadership decreased slightly. The

standard deviations of all of the subscales increased, with a dramatic change observed in Study

Skills. All the differences in mean scores are negligible, but the changes in the standard

deviations of Adaptability, Leadership, and Study Skills are of note.

22

Table 10 Mean Scores of Subscales of Internalizing Problems

Composite

Scales Subscales

Mean (Std Dev)


Positive

Group

Negative

Group

Positive

Group

Negative

Group

Internalizing

Problem 70.83 (11.25) 68.44 (13.32) 66.59 (13.25) 62.22 (10.69)

Anxiety 62.17 (13.25) 59.17 (13.00) 60.06 (12.39) 55.28 (9.00)

Depression 60.56 (11.00) 54.78 (9.32) 58.76 (12.90) 55.17 (7.16)

Somatization 77.72 (10.87) 80.44 (16.27) 70.88 (15.32) 68.94 (15.75)

Atypicality 52.83 (9.67) 52.78 (6.79) 57.65 (10.25) 53.50 (7.74)

Withdrawal 55.61 (9.11) 52.11 (11.88) 55.76 (12.14) 55.06 (12.12)

Table 11 Mean Scores of Subscales of School Problems

Composite

Scales Subscales

Mean (Std Dev)


Positive

Group

Negative

Group

Positive

Group

Negative

Group

School

Problem 57.06 (12.26) 54.72 (8.66) 51.71 (9.82) 49.94 (6.90)

Attention Problem 52.83 (9.67) 52.78 (6.79) 49.82 (8.37) 48.61 (6.71)

Learning Problem 60.00(13.91) 55.89 (9.69) 53.53 (10.57) 51.44 (7.02)

Results on Adaptive Skills are presented in Table 12. Functional Communication has the

smallest mean T score which represents the worst behavior, while Social Scales has the largest

mean T score. All the mean T scores of subscales are in the average range. In consistent with the

previous analysis for the Adaptive Skills, results from subscales further confirmed that most

children’s adaptive behaviors are good.

When the missing data were handled (Appendices A. Table 5), the mean scores of

Adaptability, Functional Communication, and Study Skills had slight increases; the mean score

of Social Skills increased over 1.0, but the mean score of Leadership decreased slightly. The

standard deviations of all of the subscales increased, with a dramatic change observed in Study

23

Skills. All the differences in mean scores are negligible, but the changes in the standard

deviations of Adaptability, Leadership, and Study Skills are of note.

Table 12 Mean Scores of Subscales of Adaptive Skills

Composite

Scales Subscales

Mean (Std Dev)


Positive

Group

Negative

Group

Positive

Group

Negative

Group

Adaptive

Skills 44.83 (8.90) 46.83 (6.91) 46.71 (10.04) 49.61 (9.06)

Adaptability 45.22 (6.44) 45.39 (5.92) 44.41 (6.47) 46.00 (8.49)

Functional

Communication 41.50 (12.32) 45.83 (9.69) 42.59 (13.69) 46.17 (9.90)

Social Skills 47.28 (9.27) 47.61 (7.96) 50.41 (10.91) 53.00 (10.66)

Leadership 47.22 (8.58) 48.33 (8.42) 49.71 (8.21) 51.00 (7.82)

Study Skills 46.39 (10.89) 48.67 (7.75) 48.12 (9.96) 52.00 (6.74)

As a helpful diagnostic procedure, the Quantile-Quantile (QQ) Plots of the Externalizing

Problems, Internalizing Problems, School Problems, BSI and Adaptive Skills by time and by

status are shown in Figure 4 and Figure 5. No obvious violations on the normal distribution

assumptions were detected.

24

Figure 4 QQ Plots by Time

25

Figure 5 QQ Plots by Status

26

To test whether there is a significant difference in composite T scores between before-

after-treatment measures, a paired-sample t test was performed. Table 13 shows the results from

the paired t-test. All the p-values of the composite scales except Adaptive Skills are less than

0.05, suggesting significant differences in children’s behaviors following treatment for

Externalizing Problems, Internalizing Problems, School Problems, and BSI. All the significant

variables are clinical scales, which measure problematic levels. These evidences indicate that the

problematic behaviors of children significantly improve after the treatment.

From the results of multiple imputation (Appendices A. Table 6), the mean differences in

all clinical scales decreased with an increasing p-value, yet still remain all-significant. For

Adaptive Skill, the mean difference increased with a lower p-value that is over 0.05. In

summary, conclusions from the testing of the difference in composite T scores following MDA

did not change after dealing with the missing data.

Table 13 Paired T-test: Before-treatment (𝑋1) vs After-treatment (𝑋2)

Variable 𝑿𝟏 − 𝑿𝟐

SE(𝑿𝟏 − 𝑿𝟐

) t d.f. p-value

Externalizing

Problem 4.00 1.34 2.97 34 0.0054

Internalizing

Problem 5.37 2.07 2.59 34 0.0139

School Problem 5.26 1.35 3.91 34 0.0004

BSI 2.89 1.37 2.11 34 0.0425

Adaptive Skill -2.43 1.34 -1.81 34 0.0784

Hotelling’s T2 test was conducted for multivariate analysis with multiple comparison

adjustments. From Table 14, we reject the hull hypothesis (F = 6.06; d.f. = 5, 30; p = 0.0005).

Results of the paired Hotelling’s T2 test indicate that the mean composite T score of at least one

of the five composite scales changed following the MDA with praziquantel.

27

Table 14 MANOVA Test and Exact F statistics

Statistic Value F Value Num DF Den DF Pr > F

Wilks’ Lambda 0.49769 6.06 5 30 0.0005

Pillai’s Trace 0.50231 6.06 5 30 0.0005

Hotelling-Lawley Trace 1.00926 6.06 5 30 0.0005

Roy’s Greatest Root 1.00926 6.06 5 30 0.0005

Simultaneous and Bonferroni 95% confidence intervals were computed for the

Hotelling’s T2 test. The mean score of the School Problems decreased by 5.26 (95% confidence

interval, 0.15858, 10.3557) following the MDA with praziquantel. Since all the remaining

intervals include zero, the mean scores of the Externalizing Problems, Internalizing Problems,

BSI and the Adaptive Skills did not change significantly following the treatment.

Table 15 Simultaneous and Bonferroni Confidence Interval:

Before-treatment (𝑋1) vs After-treatment (𝑋2)


95% confidence interval

Simultaneous Bonferroni

Externalizing Problem 4.00 (-1.09538, 9.0954) (0.33094, 7.6691)

Internalizing Problem 5.37 (-2.47891, 13.2218) (-0.28141, 11.0243)

School Problem 5.26 (0.15858, 10.3557) (1.58579, 8.9285)

BSI 2.89 (-2.30298, 8.0744) (-0.85054, 6.6220)

Adaptive Skill -2.43 (-7.49852, 2.6414) (-6.07932, 1.2222)

A profile plot was drawn to see the difference of mean composite T scores between

before- and after-treatment measures. From Figure 6, the largest difference is seen from the

Internalizing Problems, with a comparable difference observed from the School Problems as

well. The results of Hotelling’s T2 test for parallel profiles are shown in Table 15. We found

strong evidence against the null hypothesis of parallel profiles (F = 6.14; d.f. = 4, 31; p =

0.0009). The change in mean composite T scores following MDA depends on the composite

scales.

28

Figure 6 Profile Plot of Composite Scales: Before-treatment vs After-treatment

Table 16 MANOVA Test and Exact F statistics for Parallel Profiles

Statistic Value F Value Num DF Den DF Pr > F

Wilks’ Lambda 0.55813 6.14 4 31 0.0009

Pillai’s Trace 0.44187 6.14 4 31 0.0009

Hotelling-Lawley Trace 0.79170 6.14 4 31 0.0009

Roy’s Greatest Root 0.79170 6.14 4 31 0.0009

The p-value of the Adaptive Skills is not significant, yet it reaches marginal significance.

Hence, we extended analyses to the subscales of the Adaptive Skills. From Table 17, the p-value

of both Social Skills and Study Skills are significant, while the other three are not,, suggesting

different impacts on the subscales from MDA.

29

Table 17 Paired T-test for Adaptive Scales: Before-treatment (𝑋1) vs After-treatment (𝑋2)

Variable 𝑿𝟐 − 𝑿𝟏

SE(𝑿𝟐 − 𝑿𝟏

) t d.f. p-value

Adaptability -0.09 1.26 -0.07 34 0.9462

Social Skills 4.29 1.76 2.44 34 0.0200

Leadership 2.69 1.56 1.73 34 0.0940

Study Skills 2.74 1.31 2.09 34 0.0444

Functional

Communication 0.77 1.79 0.43 34 0.6689

Spaghetti plots were drawn to see the trends of child’s behaviors following the MDA.

From Figure 7, for Externalizing Problems and School Problems, the changes in the positive

group are more substantial than those observed from the negative group following treatment,

with subject-level trajectories being highly heterogeneous. For Internalizing Problem, BSI, and

Adaptive Skills, the difference of the changes between the groups with positive and negative

status is not obvious and the subject-level heterogeneity is further confirmed.

30

Figure 7 Spaghetti Plots for Externalizing Problems, Internalizing Problems, BSI, School

Problems and Adaptive Skills

31

Linear mixed effects models were built for each composite scale. From Table 17, for

status, the p-values of Externalizing Problems and BSI are significant, indicating that the average

of the mean scores for children’s behaviors in Externalizing Problems and Behavioral Symptoms

Index are significantly different for the negative and positive groups. For before- and after-

treatment comparison, the p-value of BSI is not significant from this model, while it was

significant from the previous paired t-test, indicating that an adjusted model reduces the evidence

in favor of a significant change. For the interaction Status*Time, since none of the p-values for

each composite scale is significant, changes over time doesn’t appear to differ between infected

and non-infected subjects.

Results after the multiple imputation (Appendices A. Table 7) show that, for the

comparisons between infection status, the p-values of Internalizing Problems and Adaptive Skills

had a dramatic increase while the p-values for other composite scales did not increase much. The

p-value of Externalizing Problems and School Problems are still significant, and the others are

not significant. For the before- and after- treatment comparison, similar as the results from the

status comparison, the p-values of Internalizing Problems increased a significant amount that

leads to a fundamental change in the conclusion. On the contrary, the p-value of BSI reached the

0.05 significance level after missing values were handled by multiple imputation. These results

are worthy of notice. For the interaction term, the p-values did not change significantly and no

previous conclusions from CCA were violated.

Table 18 P-values of Type 3 Tests of Fixed Effect

Effect

P Values

Externalizing

Problems

Internalizing

Problems

School

Problems

Behavioral

Symptoms Index

Adaptive

Skills

Time 0.0074 0.0142 0.0006 0.0522 0.0897

Status 0.0041 0.2632 0.3053 0.0192 0.1918

Time*Status 0.3064 0.6307 0.8296 0.3574 0.7152

32

Tables 19 to Table 23 present the solutions for fixed effects from the linear mixed effects

models fitted for the five composite scales. The P-values for the interaction terms in all five

models are not significant at the 0.05 level, reflecting a lack of evidence in support of a deviation

in the change of composite scales between the infection positive and negative subjects.

From the results after multiple imputation (Appendices A. Table 8-12), the single

estimates of Time and Time*Status changed slightly, but the overall influence of Time and

Status on each Composite T scale stayed relatively unchanged.

The fitted model can be written as:

E(Externalizing Problems) = 61.72 -5.13Time-7.11Status+2.74Time*Status

E(Internalizing Problems) = 70.83 -4.26Time-2.39Status-1.96Time*Status

E(School Problems) = 57.06 -5.35Time-2.33Status+0.58Time*Status

E(BSI) = 61.39 -3.94Time-6.00Status+2.49Time*Status

E(Adaptive Skills) = 44.83 +1.81Time+2.00Status+0.97Time*Status

Table 19 Solution for Fixed Effects of Externalizing Problems

Effect Status Estimate S.E. DF t p-value

Intercept 61.72 2.50 5 24.66 <.0001

Time After -5.13 1.88 33 -2.72 0.0102

Status Negative -7.11 2.27 33 -3.14 0.0036

Time*Status After*Negative 2.74 2.63 33 1.04 0.3064

Table 20 Solution for Fixed Effects of Internalizing Problems


Intercept 70.83 3.24 5 21.86 <.0001

Time After -4.26 2.89 33 -1.47 0.1501

Status Negative -2.39 3.56 33 -0.67 0.5072

Time*Status After*Negative -1.96 4.05 33 -0.49 0.6307

33

Table 21 Solution for Fixed Effects of School Problems


Intercept 57.06 2.98 5 19.17 <.0001

Time After -5.35 1.90 33 -2.82 0.0081

Status Negative -2.33 2.36 33 -0.99 0.3292


Table 22 Solution for Fixed Effects of BSI


Intercept 61.39 2.84 5 21.64 <.0001

Time After -3.94 1.91 33 -2.06 0.0470

Status Negative -6.00 2.33 33 -2.57 0.0148


Table 23 Solution for Fixed Effects of Adaptive Skills


Intercept 44.83 2.63 5 17.03 <.0001

Time After 1.81 1.87 33 0.97 0.3409

Status Negative 2.00 2.26 33 0.88 0.3834


Further, separate analyses with independent sample t test were carried out to test the

difference of the before-treatment and after-treatment measures between the positive and

negative groups. From Figure 8, there is no obvious trend that the mean difference of before-

treatment and after-treatment in positive group is larger than in negative group. And the results

of t test (Table 24) show that all the p-value are not significant at the 0.05 level. Thus, the change

of composite T scores following MDA is not relative to schistosomiasis status, i.e., greater in

positive group than in negative group.

After multiple imputation (Appendices A. Table 13), the mean differences in positive

group for Externalizing Problems, Internalizing Problems, and School Problems had a very tiny

decreasing while the mean differences for BSI and Adaptive Skills increased a little. In

34

comparison to other obvious increase of standard deviation after multiple imputation in other

analyses, the standard deviation in positive group almost did not change. For each confidence

interval, 0 is included, which means that there is no significant difference following MDA

between negative and positive group.

Table 24 Mean Changes following MDA

between Positive and Negative Groups

Variable

Mean Standard Error

P-value Positive Negative Positive Negative

Externalizing Problems 5.71 2.39 2.09 1.68 0.4475

Internalizing Problems 4.47 6.22 3.04 2.89 0.9275

School Problems 5.76 4.78 1.71 2.10 0.3455

Behavioral Symptoms

Index 4.41 1.44 2.00 1.87 0.8795

Adaptive Skills -2.06 -2.78 1.92 1.92 0.9203

Figure 8 Mean Changes following MDA

between Positive and Negative Groups

Additionally, two important indexes from BASC-2 are worthy of attention. One is the F

Index, aiming to test whether the distribution is highly skewed. The other is the Consistency

-4

-3

-2

-1

0

1

2

3

4

5

6

7

Externalizing

Problems

Internalizing

Problems

School Problems Behavioral

Symptoms Index

Adaptive Skills

Positive Negative

35

Index, which tests the respondent disregarded the item content. From Table 25, we notice that

some children with acceptable F index may have caution F index after the treatment, while the

caution F index could also become acceptable after the treatment for others. McNemar’s Test

statistic for F Index is 0.0769 with d.f. = 1, represented by a p-value close enough to 1. The result

suggests that there is a no significant difference from before-treatment to after-treatment with

regard to the F Index distributions.

Table 25 McNemar’s Test for F Index

Before-treatment After-treatment

Acceptable Caution

Acceptable 19 6

Caution 7 3

A parallel analysis was also performed for the Consistency index. Table 26 shows that

more children switched from Acceptable to Caution after-treatment than the other direction.

McNemar’s Test statistic for Consistency Index is 8.0667 with d.f. = 1 and p-value=0.0074. The

result suggests that there is a statistically significant difference from before-treatment to after-

treatment reflected by the Consistency Index. Overall, children tend to achieve better consistency

with their responses after-treatment than before-treatment.

Table 26 McNemar’s Test for Consistency Index

Before-treatment After-treatment

Acceptable Caution

Acceptable 8 2

Caution 13 12

Discussion

The purpose of the present study is to determine the impact of MDA with praziquantel on

children’s behaviors by using the BASC-2 Teacher Rating scales. As schistosomiasis is still

36

prevalent in many areas, especially in the sub-Saharan Africa, there is a need for early

prevention. Previously researchers [3] concluded that the schistosomiasis burden has been

underreported, and the signs and symptoms of schistosomiasis on children are non-specific.

Given these existing challenges, more efforts are demanded to protect children from

schistosomiasis. Despite much research devoted to the better understanding of the prevalence,

transmission, and subtle morbidity [2-5], few have investigated the impacts of schistosomiasis

infection and its treatment on school-age children’s behaviors. Our study seeks to fill in this gap.

The BASC-2 is an instrument commonly used in educational and psychological areas for the

assessment of children’s behaviors [6]. In this study, we applied BASC-2 to examine differences

in composite T scores on clinical and adaptive scales between children with positive and

negative status of schistosomiasis, as well as between before- and after-treatment with

praziquantel.

From the results, the change in mean scores for School Problems is most substantial, and

it is also the only composite scale reaching significance when before- and after- treatment score

are compared in both paired t-test and Hotelling’s T2 test. The findings are in consistent with

literatures reporting that schistosomiasis can directly cause a reduced ability to learn [19]. It

appears that schistosomiasis can also cause children to be aggressive and/or overly active, since

the mean differences in Externalizing Problems are highly significant not only following the

treatment, but also between the two infection status groups. Often, behaviors included in

Externalizing Problems are obvious act-out behaviors that are relatively easy for teachers to

notice, and that would partly explain the directly detected differences even with a limited sample

size. Although the change in the overall Adaptive Skills is only marginally different, the

differences in Social Skills and Study Skills following MDA are both significant. This suggests

37

that the MDA might have the largest impacts on these two adaptive behaviors. Alternatively, the

Study Skills is also considered to be highly correlated with the ability of learning, and can be

directly influence by schistosomiasis infection.

The significant results we received from paired two sample t test differ from the results

from the Hotelling’s T2 test. From the paired t test, the differences of mean scores between

before-treatment and after-treatment are significant for Externalizing Problems, Internalizing

Problems, School Problems and the BSI, all of which are clinical scales. The Hotelling’s T2 test

only detects the difference in School Problem as statistically significant, as it controls the

experiment-wise error rate and thus is relatively conservative with Bonfferoni or similar

corrections for the multiple comparison issue. Compared to the significance level (α = 0.05) used

in paired t test, Bonferroni procedure is more conservative with a significance level of 𝛼

𝑛 (n is the

total number of hypothesis tested). As a consequence, we achieved relatively conservative results

from the Hotelling’s T2 test. However, given the limited sample size in this study, we only

consider the Hotelling’s T2 test as a supplementary analysis to confirm some of the conclusions

from the previous analysis, i.e. the School Problem scale changed significantly from before- to

after- treatment. While the nice feature of controlling overall type-I error in multiple comparison

settings from the approach is well acknowledged and appreciated, it could potentially reduce the

power in small sample scenarios. Therefore, it is more appropriate to view the insignificant

results on the Externalizing Problems, Internalizing Problems, and the BSI from the Hotelling’s

T2 test as indications for follow-up confirmatory studies with larger sample size.

A higher level of heterogeneity in composite scales’ changing trajectories were observed

in the children belonging to the negative status group, with the composite T scores did not

change much for some but increase or decrease dramatically for others. The discrepancy is more

38

substantial in the Externalizing Problems and School Problems. One possible explanation is that

some children in the schistosomiasis negative group were in fact false negative, with eggs being

present but not detected from the stool.

Multiple imputation approaches were implemented as a sensitivity check for several main

statistical analyses to deal with the missing data. In general, results did not differ significantly

and most of the changes were negligible. Therefore, we conclude that the primary complete-case

analyses as presented in the main manuscript are valid and robust.

Several limitations of this study are worth noting. The sample size for this study was

relatively small, with a total of 36 students form six different schools, which may potentially

make some of the analyses underpowered. Future studies with a significantly increased sample

size are warranted to confirm our findings. With a larger sample size, conclusions on the

interaction effects between treatment and infection status could be more deterministic. In

addition, only TRS was used in this study. We believe that future studies using PRS and SRP

will certainly add more in-depth discussions on the topic. The age group of children from 8 to 11

is narrow; hence, most of the findings from the current study are only representative of the

“child” category from TRS. However, we hope that this work could pave the ways for studies

looking into the application of BASC-2 to other age groups such as “preschool” or “adolescent”

in future schistosomiasis research. The adjusted covariates in this study are very few, so findings

are subject to potential biases due to confounding. For instance, the socioeconomic status (SES)

including some quantification of family income, parental education, etc., if available, can be

included as covariates, as those have been previously reported to impact children’s behaviors

[20]. In addition, schools in closest proximity to lakes or rivers tend to have high schistosomiasis

prevalence rates [4], thus, if spatial information such as the distance from the schools to water

39

bodies can be collected and adjusted in future studies, it will enhance our knowledge in better

understanding the geographic impacts. Further, the original BASC-2 was designed for children

samples taken in the United States and Latin America [8], and this study applied the same tool to

children in Kenya Future research is demanded to verify to the validity of using BASC-2 to

assess children’s behaviors in African countries, where the culture and social economic

situations are certainly quite different.

40

CHAPTER 4

CONCLUSION

In general, children with negative schistosomiasis status have better behaviors than those

with positive status at both before- and after-treatment. All behaviors as assessed by mean T

scores from composite scales showed improvements after the mass drug administration with

praziquantel. For Externalizing Problems, Internalizing Problems, School Problems, and BSI, all

of which belonging to the clinical scales, there are significant decrease in mean composite T

scores following treatment. For Externalizing Problems and BSI, the school-age children

schistosomiasis positive obtain significantly different scores compared to children

schistosomiasis negative. The changes in composite T scores following treatment for children

with negative schistosomiasis status are not larger than those with positive status. There is also a

significant difference on Consistency Index between before-treatment and after-treatment.

41

REFERENCE

1. Schistosomiasis. (2016). Retrieved April 11, 2016, from

http://www.who.int/mediacentre/factsheets/fs115/en/

2. Samuels, A. M., Matey, E., Mwinzi, P. N., Wiegand, R. E., Muchiri, G., Ireri, E., . . .

Secor, W. (2012). Schistosoma mansoni Morbidity among School-Aged Children: A

SCORE Project in Kenya. The American Society of Tropical Medicine and Hygiene,

87(5), 874-882.

3. Davis, S. M., Wiegand, R. E., Mulama, F., Kareko, E. I., Harris, R., Ochola, E., . . . Won,

K. Y. (2015). Morbidity Associated with Schistosomiasis Before and After Treatment in

Young Children in Rusinga Island, Western Kenya. The American Society of Tropical

Medicine and Hygiene, 92(5), 952-958.

4. Odiere, M. R., Opisa, S., Odhiambo, G., Jura, W. G., Ayisi, J. M., Karanja, D. M., &

Mwinzi, P. N. (2011). Geographical distribution of schistosomiasis and soil-transmitted

helminths among school children in informal settlements in Kisumu City, Western

Kenya. Parasitology, 138(12), 1569-1577.

5. Use of Antimalarials to Reduce Malaria Transmission. (2015). Retrieved April 11, 2016,

from http://www.cdc.gov/malaria/malaria_worldwide/reduction/mda_mft.html

6. Hass, M. R., Brown, R. S., Brady, J., & Johnson, D. B. (2012). Validating the BASC-

TRS for Use with Children and Adolescents with an Educational Diagnosis of Autism.

Remedial And Special Education, 33(3), 173-183.

http://www.who.int/mediacentre/factsheets/fs115/en/

http://www.cdc.gov/malaria/malaria_worldwide/reduction/mda_mft.html

42

7. Community-University Partnership for the Study of Children, youth, and Families

(2011). Review of the Behavior Assessment System for Children –Second Edition

(BASC-2). Edmonton, Alberta, Canada.

8. Reynolds, C. R., & Kamphaus, R. W. (2004). BASC 2, Behavior assessment system for

children. Circle Pines, MN: American Guidance Service.

9. Hartley, A., Wright, J., Zakriski, A., & McCarthy, C. (n.d). The Influence of Clinical

Experience and Assessment Method on the Evaluation of Child Behavior Change.

Journal of Psychopathology and Behavioral Assessment, 36(3), 358-370.

10. Kabatereine, N., Tukahebwa, E., Kazibwe, F., Namwangye, H., Zaramba, S., Brooker, S.,

& ... Fenwick, A. (n.d). (2006). Progress towards countrywide control of schistosomiasis

and soil-transmitted helminthiasis in Uganda. Transactions Of The Royal Society Of

Tropical Medicine And Hygiene, 100(3), 208-215.

11. Donders, A., van der Heijden, G., Stijnen, T., & Moons, K. (n.d). Review: A gentle

introduction to imputation of missing values. Journal of Clinical Epidemiology, 59(10),

1087-1091.

12. Mitra, R., & Reiter, J. P. (2016). A comparison of two methods of estimating propensity

scores after multiple imputation. Statistical Methods In Medical Research, 25(1), 188-

204. doi:10.1177/0962280212445945

13. Van Buuren, S. (2007). Multiple imputation of discrete and continuous data by fully

conditional specification. Statistical Methods in Medical Research, 16(3), 219.

14. SAS Institute Inc. (n.d.). SAS (Version 9.4) [Computer software], Cary, NC

43

15. Freeman, J., & Modarres, R. (2006). Efficiency of t -Test and Hotelling's T2 -Test After

Box-Cox Transformation. Communications In Statistics: Theory & Methods, 35(6),

1109-1122. doi:10.1080/03610920600672203.

16. Burton, P., Gurrin, L., & Sly, P. (1998). Extending the simple linear regression model to

account for correlated responses: an introduction to generalized estimating equations and

multi-level mixed modelling. Statistics in Medicine, 17(11), 1261-1291.

17. Muth, C., Bales, K. L., Hinde, K., Maninger, N., Mendoza, S. P., & Ferrer, E. (2016).

Alternative Models for Small Samples in Psychological Research: Applying Linear

Mixed Effects Models and Generalized Estimating Equations to Repeated Measures

Data. Educational And Psychological Measurement, 76(1), 64-87.

18. The Difference Between a Chi-Square Test and a McNemar Test. (n.d.). Retrieved April

27, 2016, from http://www.theanalysisfactor.com/difference-between-chi-square-test-

and-mcnemar-test/

19. Epidemiological situation. (n.d.). Retrieved April 27, 2016, from

http://www.who.int/schistosomiasis/epidemiology/en/

20. Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic Status and Child Development.

Annual Review of Psychology, 53, 371-399.

http://www.theanalysisfactor.com/difference-between-chi-square-test-and-mcnemar-test/

http://www.theanalysisfactor.com/difference-between-chi-square-test-and-mcnemar-test/

http://www.who.int/schistosomiasis/epidemiology/en/

44

APPENDICES A

MULTIPLE IMPUTATION RESULTS

Table 1 Mean Composite T Scores after Treatment (by Imputation)

Status

Mean (Std Dev)

Externalizing

Problems

Internalizing

Problems

School

Problems

Behavioral

Symptoms Index

Adaptive

Skills

Negative 52.22 (4.83) 62.22 (10.69) 49.94 (6.90) 53.94 (6.92) 49.61 (9.06)

Positive 56.44 (8.87) 66.83 (13.67) 51.75 (10.17) 57.01 (10.01) 47.10 (11.04)

Table 2 Mean Scores of Subscales of Externalizing Problems (by Imputation)

Composite

Scales Subscales

Mean (Std Dev)


Positive

Group

Negative

Group

Positive

Group

Negative

Group

Externalizing

problem 61.72 (11.74) 54.61 (8.17) 56.44 (8.87) 52.22 (4.83)

Hyperactivity 59.17 (10.07) 52.78 (6.20) 54.43 (8.78) 51.61 (4.77)

Aggression 64.89 (13.53) 56.44 (12.25) 57.98 (8.43) 54.56 (7.25)

Conduct Problem 58.78 (12.98) 53.50 (7.33) 55.39 (13.41) 50.06 (4.39)

Table 3 Mean Scores of Subscales of Internalizing Problems (by Imputation)

Composite

Scales Subscales

Mean (Std Dev)


Positive

Group

Negative

Group

Positive

Group

Negative

Group

Internalizing

Problem 70.83 (11.25) 68.44 (13.32) 66.83 (13.67) 62.22 (10.69)

Anxiety 62.17 (13.25) 59.17 (13.00) 60.70 (15.31) 55.28 (9.00)

Depression 60.56 (11.00) 54.78 (9.32) 58.52 (13.00) 55.17 (7.16)

Somatization 77.72 (10.87) 80.44 (16.27) 71.30 (16.17) 68.94 (15.75)

Atypicality 52.83 (9.67) 52.78 (6.79) 56.13 (13.64) 53.50 (7.74)

Withdrawal 55.61 (9.11) 52.11 (11.88) 56.28 (15.61) 55.06 (12.12)

45

Table 4 Mean Scores of Subscales of School Problems (by Imputation)

Composite

Scales Subscales

Mean (Std Dev)


Positive

Group

Negative

Group

Positive

Group

Negative

Group

School

Problem 57.06 (12.26) 54.72 (8.66) 51.75 (10.17) 49.94 (6.90)

Attention Problem 52.83 (9.67) 52.78 (6.79) 49.75 (9.09) 48.61 (6.71)

Learning Problem 60.00(13.91) 55.89 (9.69) 53.60 (11.09) 51.44 (7.02)

Table 5 Mean Scores of Subscales of Adaptive Skills (by Imputation)

Composite

Scales Subscales

Mean (Std Dev)


Positive

Group

Negative

Group

Positive

Group

Negative

Group

Adaptive

Skills 44.83 (8.90) 46.83 (6.91) 47.10 (11.04) 49.61 (9.06)

Adaptability 45.22 (6.44) 45.39 (5.92) 44.87 (9.43) 46.00 (8.49)

Functional

Communication 41.50 (12.32) 45.83 (9.69) 42.81 (15.45) 46.17 (9.90)

Social Skills 47.28 (9.27) 47.61 (7.96) 51.65 (13.07) 53.00 (10.66)

Leadership 47.22 (8.58) 48.33 (8.42) 48.99 (11.51) 51.00 (7.82)

Study Skills 46.39 (10.89) 48.67 (7.75) 48.79 (15.45) 52.00 (6.74)

Table 6 Paired T-test: Before-treatment (𝑋1) vs After-treatment (𝑋2) (by Imputation)


SE(𝑿𝟏 − 𝑿𝟐

) t d.f. p-value

Externalizing

Problem 3.84 1.33 2.90 35 0.0064

Internalizing

Problem 5.25 2.06 2.58 35 0.0142

School Problem 5.14 1.33 3.89 35 0.0004

BSI 2.77 1.36 2.06 35 0.0468

Adaptive Skill -2.47 1.34 -1.87 35 0.0698

46

Table 7 P-values of Type 3 Tests of Fixed Effect (by Imputation)

Effect

P Values

Externalizing

Problems

Internalizing

Problems

School

Problems

Behavioral

Symptoms Index

Adaptive

Skills

Time 0.0176 0.2006 0.0132 0.0365 0.3338

Status 0.0027 0.5080 0.3317 0.0137 0.4088

Time*Status 0.3223 0.6030 0.8549 0.2984 0.8677

Table 8 Solution for Fixed Effects of Externalizing Problems (by Imputation)


Intercept 61.72 2.53 5 24.38 <.0001

Time After -5.28 2.20 34 -2.40 0.0176

Status Negative -7.11 2.37 34 -3.00 0.0027


Table 9 Solution for Fixed Effects of Internalizing Problems (by Imputation)


Intercept 70.83 3.28 5 21.62 <.0001

Time After -4.00 3.12 34 -1.28 0.2006

Status Negative -2.39 3.61 34 -0.66 0.5080

Time*Status After*Negative -2.22 4.27 34 -0.52 0.6030

Table 10 Solution for Fixed Effects of School Problems (by Imputation)


Intercept 57.06 3.00 5 19.03 <.0001

Time After -5.30 2.13 34 -2.49 0.0132

Status Negative -2.33 2.40 34 -0.97 0.3317


Table 11 Solution for Fixed Effects of BSI (by Imputation)


Intercept 61.39 2.84 5 21.65 <.0001

Time After -4.38 2.08 34 -2.10 0.0365

Status Negative -6.00 2.43 33 -2.47 0.0137


47

Table 12 Solution for Fixed Effects of Adaptive Skills (by Imputation)


Intercept 44.83 2.67 5 16.82 <.0001

Time After 2.27 2.34 34 0.97 0.3338

Status Negative 2.00 2.42 34 0.83 0.4088


Table 13 Mean Difference of Before-treatment and After-treatment

between Positive and Negative Groups (by Imputation)

Variable

Mean Standard Deviation 95% Confidence

Limits Positive Negative Positive Negative

Externalizing

Problems 8.04 5.5 6.32 5.00 (-4.36, 20.43)

Internalizing

Problems 10.62 11.78 7.54 6.70 (-4.16, 25.40)

School Problems 7.37 8.11 5.33 5.85 (-3.08, 17.82)

Behavioral Symptoms

Index 7.62 6.56 5.28 4.44 (-2.72, 17.97)

Adaptive Skills 6.40 6.56 5.04 5.36 (-3.48, 16.29)

Documents

ASSESSMENT OF CHILDREN’S BEHAVIOR BEFORE AND AFTER …