Asthma: a Leading Cause of Absenteeism in Schools - Research Proposal Example

The paper 'Asthma: a Leading Cause of Absenteeism in Schools' is an excellent example of a research proposal on health science and medicine.
Asthma is a respiratory condition that compromises the functionality of the airway through obstruction associated with continuous instances of breathlessness and wheezing. The condition is prevalent amongst the school-going children between the ages of 8 to 11 years. Researchers endeavor to provide a remedy to the situation by developing medicines to curb the condition effectively. However, the condition has shown its persistence in spite of the ongoing research to mitigate it. This research intends to determine the predetermined hypothesis outlining that Asthma is the leading cause of absenteeism in schools and the third reason for hospitalizations in children (Houser, 2014).

This is quantitative research as it gives a clear relationship between the variables relevant to the issue of discussion. In this case, the descriptive date bringing out the relationships between the demographic factors such as age and race to be influential in the determination of asthma in an individual. The research also gives out the numerical values pertaining to the collected data. According to the intention of the researcher, this is quasi-experimental research as it involves the guidance from the hypothesis. In addition, it is research on the science dealing with biological functionality in the respiratory system of school-age children.

The researcher specifically involved an experiment in finding out the clear picture of the study. As it stands out, there was the involvement of social interactions in which the investigator met with the children and their caretakers. As per the design, this research is classified as conclusive research as it gives data that is subject to quantitative analysis such as the descriptive data. This is conclusive research because it depends on large quantity samples and also is subject to quantitative analysis.

The researchers recruited their subjects based on age and gender. The school-age children selected were between the ages of 8 and 11. This was done as it carried the best sample to be used by the researchers. The independent variables according to this article are demographic factors such as gender, age, and race. The dependent variables are factors such as learning experiences, access to computer and family structure.     

Asthma was the confounding variable. The confounding variables are those that lead to a problem since it is empirically connected to both the dependent and independent variables. This is the type of variable that is understood as a variable rather than that with the possibility of being a problem. The participants in the study included children, parents and research groups. The accessible population was the participants included while the target population was the participants not included in the study. The target population was not included because they were not accessible during the study.

Measurement tools

Assessment center: this is an online tool for obtaining the patient data safely together with the capability to include customized instruments.

Atlas of IBHC: embraces the faculty of assimilated interactive health care determination.

Education Resources Information Center: The world’s biggest database of education materials including all documentation and journal resources.

Google and or Yahoo: the search engine on the internet.

Nursing Reference Center: inclusive reference apparatus for clinical nurses as well as documents providing explanations of research tools, clinical evaluation tools, psychosomatic tests, and approach measures.

The research biases identified by the authors were selection bias and publication bias. The selection bias can result in the process of identification of the population to study. There are also significant problems in the identification of unpublished studies.

Selection bias or effect is the selection of entities, groups or information for evaluation such that appropriate randomization is not attained, in so doing making sure that the sample acquired is not demonstrative of the population anticipated to be investigated (Houser, 2014).

Controlling bias

Reflexivity: refers to the researcher’s personal reconsiderations of notions together with the predispositions (Houser, 2014).

Negative case sampling that demands purposively search for and, if available, sensibly scrutinize cases that criticize your anticipations.

The authors never realized the confirmation bias experienced and presumed that it was a social skill that could boost credibility in the research (Houser, 2014).

Limitations

History threat: any occasion, apart from the premeditated treatment scenario, that results amid the pretest and posttest dimension and has an effect on the dependent variable. The researcher will never determine whether the realized disparity between the pretest and posttest is as a result of the treatment or the historic event since both events are confounded (Houser, 2014).

Maturation threat: in case the maturation effect is confounded than the alteration observed might never be determined from the pretest to posttest originates from the treatment or maturation.

 Minimizing Measurement Errors

1. Identify the target population
2. Proper design of a questionnaire to meet the desired criteria

• Avoidance of interviewer bias

1. Mitigation of respondent bias
2. Elimination of processing errors
3. Roper interpretation of results

• Benchmarking

Results

Type of statistical analyses performed and Reasons

Correlation: to ascertain relationships between variables

ANOVA: to distinguish the means of groups after consideration of the variance

Regression: to determine the relationships between changes in variables

Analysis of descriptive data

Descriptive data can be analyzed through the evaluation of measures of central tendency that are means of explaining the central point of frequency dispersal of group data. The data can also be analyzed by determining how the scores are spread out. 

Conclusion

This research has succeeded in confirming the alternative hypothesis besides realizing its sole objective. According to the evaluation provided herein, Asthma is the leading cause of absenteeism in schools and the third reason for hospitalizations in children (Houser, 2014). Research studies have shown that asthma is consistent in its mutation and prevalence amongst the children regardless of the inventions of the cure. Most children fail to go to school occasionally due to their asthmatic conditions (Houser, 2014).