Data Analysis and Results
Childhood obesity affects approximately 20% of American children and adolescents, although various projects and policies are developed to reduce the rate of affected people (Hales et al., 2017). It has been found that children gain dietary habits observing their parents’ behaviors, so parents play a major role in shaping their children’s eating behaviors (Davidson & Vidgen, 2017). Liu et al. (2018) noted factors as parental involvement in their children’s lives and their awareness of obesity and prevention strategies are instrumental in decreasing this disorder’s prevalence. However, it has also been acknowledged that cultural peculiarities of diverse groups have a considerable impact on the way they see health and wellness (Mech et al., 2016). This direct practice involvement (DPI) project was concerned with the evaluation of the effectiveness of the educational intervention, a modified Parent Training Program developed by Slusser et al. (2012), aimed at decreasing childhood obesity in low-income Hispanic students of elementary schools.
The project involved the implementation of the educational study for parents of Hispanic elementary-school children diagnosed with obesity. The quantitative methodology was employed to address the goals of the project. The modified educational sessions developed by Slusser et al. (2012), the Parent Training Program, were held during one month. This project was carried out during a shorter period; hence, the sessions were shorter, and the meetings were more frequent as compared to the program developed by Slusser et al. (2012). In order to identify the impact of the intervention on children’s health status, children’s BMI was measured, and their parents completed physical activity questionnaires and self-reported body weight (SRBW) questionnaires. The clinical question guiding this DPI project was formulated in the following way:
For parents of elementary school-aged Hispanic children from low-income families, will Parent Training Program, compared to no intervention be effective in controlling and decreasing the BMI in one month?
Chapter 4 presents the results of the project and includes the following sections: descriptive data, data analysis procedures, results, and summary. The chapter starts with a brief introduction, followed by the provision of descriptive data and the description of data analysis procedures. The following section is devoted to the results that are presented in the textual and visual forms. The chapter ends with a summary of the major points discussed in this part of the paper. Finally, a brief introduction to Chapter 5 is provided as well.
Descriptive Data
The purpose of this project was to explore the effect of the modified Parent Training Program that was provided to parents of Hispanic elementary-school children residing in Charlotte, North Carolina. The setting for this project was a healthcare facility in Charlotte, North Carolina. The participants attended nine sessions that were held in a clinic in Charlotte, North Carolina, during a month. Overall, 40 people participated in the project; these were parents of 20 male and 20 females elementary-school Hispanic children. Power analysis was implemented to identify the appropriate sample size for this DPI project. The type I error was 5% and power value was 0.8. The minimal sample size to be included was 32 participants, so 40 people were recruited to take part in the project. The inclusion criteria were children’s BMI, race, and age, as well as parents’ gender and socioeconomic status. One parent from each family took part in the project. Low-income Hispanic families who resided in Charlotte, NC, took part in the study.
Such demographic data as gender, household income, dietary habits, and physical activity are described (see Table 1). This information is needed to identify the level of physical activity and dietary habits of children before the commencement of the project. These demographic surveys contributed to the validation of the questionnaires concerning children’s physical activity. Household income is a measure associated with the socioeconomic status of families that has a direct impact on families’ lifestyles and eating habits (Fradkin et al., 2016). Families who have low income have limited budgets and can hardly satisfy their families’ needs related to healthy diets. Employment is the information that can predict the family’s income and the time the parent spends with the child or is involved in household routine.
Table 1. Demographic Data.
Apart from the profile mentioned above, parents also provided some data regarding their eating habits and physical activity. Although the PAQ-C tool included the information associated with their children’s physical activity, this brief survey shed light on parents’ lifestyle. The findings will be briefly discussed in the following chapter, and the link between parents’ behaviors and their children’s health outcome (if any) will be considered and brought in the context of the current literature. The participants completed questionnaires related to demographic information with some clarifications. These questionnaires contained notes as to the consumption percentage mentioned in the survey. They were asked to identify the approximate amount (percentage) of different kinds of products their children consume a day. As for the physical activity measurements, there was a note in the questionnaires that explained the entries. A little exercise meant some physical activity (long-distance walking, jogging, running, jumping, playing sports games, gym) less than two hours per day. Some exercise was described as being engaged in the aforementioned activities during three hours a day. Sufficient activity stood for being engaged in some kinds of physical activity during over four hours per day.
Data Analysis Procedures
The purpose of this DPI project was to decrease the level of childhood obesity among Hispanic elementary-school children by training their parents to establish proper dietary behaviors and lifestyles in their families. The clinical question that was instrumental in achieving the goal of the project is:
For parents of elementary school-aged Hispanic children from low-income families, will the Parent Training Program, compared to no intervention be effective in controlling and decreasing the BMI in one month?
The inferential analysis was employed in order to identify the relationship between the dependent and independent variables. It was essential to detect the extent to which the independent variables affected the dependent ones. The correlational analysis was instrumental in addressing this objective, and this data analysis procedure was commonly used for quantitative quasi-experimental studies (Braden et al., 2015). The dependent variables were children’s health status and physical activity; the independent variables included parent’s awareness of childhood obesity, its peculiarities, and prevention, as well as parental involvement in the training program. The correlation between the variables was expected to show the degree of effectiveness of the training progress and its relevance in addressing childhood obesity. The analysis significance level was established at p < 0.05.
The data was collected with the help of such tools as SRBW and SRBH, as well as PAQ-C. The demographic data questionnaires were completed before and after the implementation of the educational intervention. First, this approach validated the results, and the completion of the survey at the end of the project ensured documenting any changes among the participants as some of them withdrew from the project. Multiple completion of the demographic questionnaire was helpful in the process of data editing that will be discussed below. After the participants have completed the questionnaires, their answers were reviewed, which is important as people often make errors when filling in such survey tools, which can lead to the results lacking reliability and validity (Creswell, 2014). The participants received the questionnaires with the uncompleted parts highlighted in red. Raw data were coded and organized in tables to be entered into the Statistical Package for the Social Sciences (SPSS) that was utilized to identify the relationship between the dependent and independent variables. Such demographic data as household income was also coded, which improved the data analysis process by making it more efficient.
The validity of the chosen analysis procedures is high although some measures are characterized by limited validity. For instance, BMI tends to be misleading in some cases due to the lack of focus on bone density or muscle mass. SRBW and SRBH are protocols characterized by a high degree of validity (93% of accurateness) (Olfert et al., 2018). The reliability of SRBW and SRBH, children’s BMI was also analyzed. The PAQ-C is also a valid tool, which is evident from its Cronbach’s α coefficient (α = 0.76) (Benítez‐Porres et al., 2016). The reliability of the PAQ-C was identified with the help of intraclass correlation coefficients (0.96) (Benítez‐Porres et al., 2016). Therefore, the employed data analysis instruments have sufficient reliability and validity.
Results
The project aimed at exploring the impact the educational intervention provided to parents of low-income Hispanic elementary-school children on these children’s BMI. The clinical question set was as follows: For parents of elementary school-aged Hispanic children from low-income families, will Parent Training Program, compared to no intervention be effective in controlling and decreasing the BMI in one month?
The analysis identified a direct correlation between parental involvement and their children’s BMI. Parental training led to an increase in their awareness regarding the disorder and its prevention and certain decrease in children’s BMI (see Figure 1). The mean BMI percentile of the children participating in the project decreased after the termination of the educational intervention. The percentage of the time spent on some kind of physical activity increased one month after the start of the intervention. The significance level for the present inferential analysis was established at p<0.05.
Summary
The purpose of the project was to evaluate the impact of the training program provided to parents on their children’s BMI and physical activity. The inferential analysis was the most appropriate statistical tool in this case, as it is instrumental in identifying the correlation between variables. A linear regression analysis was utilized to identify the linear relationship between the parents’ participation in the intervention and children’s body weight. The data analysis procedures included the use of the Statistical Package for the Social Sciences (SPSS). The dependent variables were children’s BMI and physical activity, while the independent variables were their parents’ awareness of obesity and its prevention, as well as their involvement in the educational intervention. The data collected with the help of a demographic questionnaire, SRBW and SRBH, and PAQ-C were coded and analyzed with the help of the appropriate statistical software, SPSS. The analysis of the data unveiled a direct link between parents’ participation in the project and their children’s health condition.
These findings, as well as their implications for the clinical practice, will be discussed in Chapter 5. This segment of the paper will include a discussion of the relationships identified between the variables, and the links between the demographic data and dependent variables. The implications for the use of the training program will be considered as well. The chapter will close with a narrative regarding the project’s implications for the clinical setting and the way it can facilitate the development of the healthcare system and public health.
References
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Braden, A., Strong, D., Crow, S., & Boutelle, K. (2015). Parent changes in diet, physical activity, and behavior in family-based treatment for childhood obesity. Clinical Pediatrics, 54(5), 494-497. Web.
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks, CA: SAGE
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