The variables represent an essential part for the realization of this social work research that aims to have certain valid evidence as to why boys are diagnosed with ADHD more than girls during their school age years as it is important to note those needed factors in order to classify and discuss a number of variables for this research work. The variables are those of the observable behaviors at school that can be measured and manipulated by any type of procedure or experiment that will give emphasis to the process of research in terms of its methodology. These observable behaviors are to be observed and justified in terms of different classroom environments.
The minor variables could refer to extraneous variables such as the classroom atmosphere and temperature during classes as well as the teacher attitude towards the handling out of the child having ADHD in the process.
The major variables to be measured in this study that will impact on the behavior that will lead to the implication and prevalence of being diagnosed with ADHD involves the children's daily school performance in terms of how they respond academically to class based on their intelligence and or IQ estimates, study habits, classmate/peer relationships, family support, level of motivation and self-Esteem
Definition of the Variables
Classroom Atmosphere and Temperature – classroom atmosphere and temperature is identified as a type of variables that can be a factor why boys are diagnosed with ADHD more than girls since, everyday these children tend to adjust themselves for the reality that atmosphere in the classroom is changing and not in its steady motion that in a way affect the child's behavior towards schooling.
Teacher Attitude – this involves how the teacher interacts and treats his students experiencing ADHD problem as this is also a factor because a child with ADHD may respond poorly or fairly to the classroom lessons and activities as it depends on the mode of strategy given by the teacher reflecting his attitude for such case mentioned.
School Performance – refers as to how students with ADHD are performing at school at any given time without structured and directed activities.
Academic Response – this involves as to how students respond academically through tests and examinations be it in oral and written exercises
Intelligence/ IQ Estimates – this embraces the total range of mental ability and capacity of a student with ADHD if he entails a low IQ or high IQ or median
Study Habits – this involves how ADHD students adopt to their study attitude towards class and how they accept it as it is such as doing home assignments for the next school day, or why they excel in Math and poor or fail in History or English
Peer Relationships – how the students accept the presence of peers and classmates around them, how they behave in team building and group activities could possibly engage into better peer relationships at school.
Family Support – this is the most crucial variable in dealing to children with ADHD especially in boys not just family is a social unit in the society but a family is a shelter wherein these children finds love, care and support and failure for this may increase the state of disorder within the affected children
Level of Motivation – this refers to a desired pattern of achieving a positive drive for the children at school through the process of constructive and healthy reinforcement without any biases such as in giving distinctions and rewards.
Level of Self-Esteem – this implies a matter of confidence within the child at school that amicably involves as to how they are dealing with themselves in the school as it can be justified by means of their attitude and behavior towards a particular situation that establishes a path to relate to their actual behavior in shaping out their real self, the type of person they are embraced by their unique personality.
Description of the Measurement of the Variable
The variables are measured in terms of nominal and ordinal pattern through the use of a specific type of scale measurement within the process, the variables are seen to be a part of attitude and behavior so, there is a need for a comparative analysis between boys with ADHD and girls with ADHD as it is a useful process of measurement as to why are boys diagnosed with ADHD more than girls through scaling measurement in terms of Likert scale as well as the use of the T- test in table having the comparison of boys with ADHD and girls with ADHD and the measurement of those respected variables mentioned earlier in this study. The nominal and ordinal collection of data relates to the DV and IV in support to the major variables as well as minor variables with the concept of formulation and execution in proper measurement.
Variable to be measured by a Scale
The variable to be measured by a scale is their level of self-esteem as it serves as one of the relevant factor that can be assessed and evaluated in finding out why boys are diagnosed with ADHD more than girls based on the level of their self-esteem.
Likert scaling, introduced Rensis Likert is the most widely used method of measuring personality, social and psychological attitudes (Babbie, 1998; Nunnally, 1978) such as the prominent measures of self-esteem have used Likert scales to make operational the underlying latent construct (Hill & Hood, 1999; Raja & Stokes, 1998; Robinson, Shaver, & Wrightsman, 1991). In addition to numerous established measures, a review of the social work literature reveals that researchers commonly use Likert scales in the development of new instruments that tap a broad array of constructs. Likert scales have been used to measure children as well as adolescent concerns that foster runaway behavior (Springer, 1998); clients' perceptions of social work interventions in school care programs (Julia, 1993) willingness to seek help (Cohen, 2000) attitudes toward disorders (Ommundsen & Larsen, 1998). The popularity of Likert scales can be traced to a number of factors, including ease of construction, intuitive appeal, adaptability and usually good reliability (Babbie, 1998; Nunnally, 1978). Likert scales present individuals with positively or negatively stated propositions and solicit respondents' opinions about the statements through a set of response keys.
The measured population will be boys with ADHD
They are asked to indicate their level of agreement or disagreement with a proposition on a graded four or five-point scale such as strongly disagrees, disagree, agree, strongly agree. Thus, creating an index that indicates the degree to which the respondent exhibits the traits in question (Duncan & Stenbeck, 1987; Roberts, Laughlin, & Wedell, 1999). A normal distribution has both positive and negative numbers. Likert response scales can perhaps best be understood numerically as positive integers (agreement) and negative integers (disagreement). In other words, no opinion or a neutral sentiment is equivalent to zero and larger positive integers are associated with higher levels of agreement Research has demonstrated that respondents may use numbers as a guide to interpretation of the sentiment; consequently, numbers are frequently incorporated into item design (Schwarz, Knauper, Hippler, Noelle-Neumann, & Clark, 1991). Assuming normality for the concept being measured results in a bell-shaped distribution. From a theoretical perspective, there is a curvilinear distribution on each side of zero sloping down to 2 and -2, respectively.
Why this Scale?
Researchers have attempted to address the problem of multiple dimensions by separating the cognitive and affective dimensions into two discrete response keys, one that asks participants to indicate whether they agree or disagree with the proposition and the other which asks participants whether they feel strongly or not strongly about the statement. Analysis of the two-question approach suggests little improvement (Brody & Dietz, 1997). Likert items do not produce dimensional ordinal responses, thus violating a central measurement tenet. Thus, a rough five-point ordinal scale has been converted into apparent interval- or ratio-level data that are presumed to be suitable for analysis with, for example, multiple regression (Byrne, 1998; Duncan & Stenbeck, 1987). It is unclear how ordinal data are transformed into interval- let alone ratio-level data merely through the summation process, interval data comprise equal or uniform units of measurement such as degrees of temperature (Russell & Bobko, 1992). Ordinal items contain less information than interval items that contain less information than ratio items. Consequently, it is possible to collapse higher levels of information into lower levels by discarding some of the obtained information. Interval data, for example, may be reduced to ordinal-level data. An ordinal measure cannot be converted into an interval one (Babble, 1998), in the form of more items, there is no guideline as to how the distance between any two values is affected.
The independent variable is Self-Esteem as it may have an effect to the other variables in the process.
The dependent variables will be the student's school performance in terms of academic achievement, intelligence study habits, classmate/peer relationships, family support and level of motivation as it can be manipulated by the independent variable.
ADHD is defined as a "persistent pattern of inattention and/or hyperactivity-impulsivity that is more frequent and severe than is typically observed in individuals at a comparable level of development." (Mayo Clinic, 2000) that contributes to the growing body of evidence that boys are at greater risk for neurodevelopmental disorders compared with girls the reason as to why males are at higher risk for these disorders remains to be unclear. ADHD is developmental disability with a number of characteristic behaviours that includes poor attention span, restlessness and a difficulty playing quietly.
Most boys have a combined type of ADHD, where they have both hyperactive impulsive and inattentive symptoms. Boys have what people generally think of as ADHD. They're overactive. They're getting up all the time in class. They're fidgety. They're inattentive. Some of these behaviors, like touching and talking to other kids, create behavioral problems or disorder in the classroom. So, they're more likely to come to the attention of teachers and parents earlier on. In a classroom, this type can be more subtle because kids with the primarily inattentive type don't have behavior problems. These kids can be very quiet and unnoticed even more if the child has at least average intelligence and they're doing reasonably well early on, when there are no huge academic challenges.
The proposal is descriptive at the same time explanatory in the sense that it tries to give importance on important discussions with regards to research study in terms of its methodology within the assumption of the needed variables that will have to complete the purpose, finalize data and information and realize the concept and usage of different variables that will form the context structure of the study. It then provides the basic ideas as how the study will be in terms of its reliability and validity proving out research evidence and findings that serves as the crucial tool for any critical analysis needed for justification and effectiveness of the study within the substantial accuracy of factual basis for research respectively.
The target population will consists of boys with ADHD and girls affected by the prevalence of ADHD to be evaluated for the process of comparison and scaling, the age bracket should be 7-12 years old under their elementary schooling age from a specialized school or institution that caters this kind of disorder in children.
The participants are twenty seven boys and girls diagnosed in ADHD schools as having ADHD according to DSM-IV criteria and 15 typical control children. The children with ADHD exhibited at least six of the nine symptoms on either the inattentiveness factor or the hyperactive-impulsive factor of the ADHD-IV Rating Scale (DuPaul et al., 1998). All children were in first, second, or third grade. The mean age of the ADHD group was 8.19 years (SD = 1.2), and that of the control group was 7.96 years (SD = 0.55). The age difference between the two groups was not significant (p = .276). Parents of all children were asked to complete the ADHD-IV Rating Scale (DuPaul et al., 1998). Scores for the inattentiveness and the hyperactivity impulsivity factors were determined by summing the scores given for the odd and even items, respectively.
Participants in the ADHD group fulfilled the diagnostic criteria for ADHD on at least one of these factors, whereas no child in the control group had scores that approached the requirements for diagnosis (inattention: 13 vs. 3.33 for ADHD and control, respectively, t-test p = .000; hyperactivity-impulsivity: 13 vs. 2.78, respectively, t-test p = .000). Twenty ADHD group children met the DSM-IV criteria for ADHD combined subtype (14 boys and 6 girls), and 7 children met the DSM-IV criteria for the inattentive subtype (6 boys and 1 girl). There were 9 girls and 6 boys in the control group and 7 girls and 20 boys in the ADHD group. Only five of the ADHD participants were under regular medication. For these participants, medications were not in use during the days of testing. All children in both groups were of average intelligence, as indicated by IQ scores higher than 80 based on an abbreviated version of the Wechsler Intelligence Scale for Children, third edition (WISC-III; Wechsler, 1991), consisting of two subtests, Vocabulary and Block Design, which compose a reliable short form (Sattler, 1992). There were no significant differences between the two groups (Vocabulary, p = .28; Block Design, p = .029). Two types of comparisons should be conducted.
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