Week 8 discussion

Week 8 discussion


Anxiety symptoms in children aged 3 to 11 may be reduced with cognitive behavioral therapy provided by the CATC program, which also provides families with techniques for creating an environment where children can thrive (Fisak et al., 2019). Also, with the help of the WBHA, the ASATP initiative has been launched. As a consequence of this initiative, researchers will examine statistics on drug addiction in people between the ages of 18 and 64. Motivational interviewing is used as a kind of treatment by the program. This article will conduct statistical analysis to identify the relationship between suggested programs and intervention, including the measurement scale of the variables that need to be investigated and the statistics required to interpret the data.

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Children’s Anxiety Treatment Center (ages 3 -11)

A descriptive analysis of data from an open trial of children treated with Anxiety Treatment will be conducted. To guarantee that patients are benefitting from therapy, quantitative data on adherence and improvement will be analyzed. Qualitative data will be analyzed for themes relating to usability and treatment satisfaction, and a coding approach will be devised to facilitate this analysis (Crowder et al., 2017). Qualitative data analysts will use content analysis approaches to code interviews (i.e., sorting and classifying material based on themes in a systematic manner). For data sorting and coding, “QSR’s NVivo 9 qualitative data analysis software will be utilized (Crowder et al., 2017). Monitoring of adverse events will be carried out throughout the open trial. A descriptive analysis will be performed on the survey data collected from therapists. Parent and Child Report Measures will be used. Spence’s Child Anxiety Scale is designed to assess the symptoms of anxiety in children. A 0 (never) to 3 (always) point scale is used to answer the 44 items on the self-report measure. Although the scale has been used in several research throughout the globe, Fink (2014) claims that its psychometric properties have been adequately evaluated.

Adult Substance Abuse Treatment Program (ages 18 – 64)

Using a basic ANOVA is the best way to analyze the data in this study since it may be used to examine three or more separate groups (King, Li & Hser, 2017). A screening tool might be compared to a survey or direct observation findings, for example, to see any discrepancies. Measured variables and latent variables are the sorts of variables that will be examined statistically. Variables that cannot be seen directly but must be inferred from observable ones are known as latent variables (King, Li & Hser, 2017). Observed variables, such as questions on a survey, are examples of measured variables. Measurements of latent variables are more trustworthy when they are connected to the latent variable in a basic ANOVA model. It is assumed that individuals are randomly assigned to conditions, independent observations are made, valid measurements are used, and all data are included in the model (Fink, 2014). It is possible to use the model to estimate program impacts at each subsequent measurement wave once the baseline measurement is taken into account (Duke et al., 2018).

Multi-item standardized measures will be used to examine adults’ knowledge and comprehension of physical and emotional development, which will measure substance abuse symptoms. Before (pre-test) and after the intervention (post-test) will be completed by the adult, depending on the assessment team’s decision. Substance abusers’ medical, legal, family/social, and mental health statuses will be assessed using a multi-item standardized test (Duke et al., 2018).


For the aim of this study, various new statistical approaches for the treatment of children’s anxiety and the prevention of adult drug usage were discussed. Methods for extracting additional information and adjusting for the special characteristics of CATC or ASAPT research data have been detailed in this study. In this way, they may help researchers get more accurate findings from their studies. However, the most significant features of the two WBHA programs are the quality of the research topic and the concept motivating the study. These problems may be answered using statistical measures.





















Crowder, M. J., Kimber, A. C., Smith, R. L., & Sweeting, T. J. (2017). Statistical analysis of reliability data. Routledge.

Duke, A. A., Smith, K. M., Oberleitner, L., Westphal, A., & McKee, S. A. (2018). Alcohol, drugs, and violence: A meta-meta-analysis. Psychology of violence8(2), 238.

Fink, A. (2014). Evaluation fundamentals: Insights into program effectiveness, quality, and value. Sage Publications.

Fisak, B., Persad, L., Gallegos, J., & Barrett, P. (2019). Prevention of anxiety in preschool-aged children. Anxiety in Preschool Children, 215–237. https://doi.org/10.4324/9781315213828-10

King, A., Li, L., & Hser, Y.-I. (2017). Common statistical methods for primary and secondary analysis in Substance Abuse Research. Research Methods in the Study of Substance Abuse, 81–112. https://doi.org/10.1007/978-3-319-55980-3_5