1.     What is your research question?

a.      To what extent does a history of sexual abuse affect the permanency outcomes for foster youths?

 

2.     Identify your key variables and provide an operational definition for each of them.

a.      In this research, the dependent variable would be permanency outcomes. With this variable the operational definitions are a. adoption, b. reunification with birth parents or relatives, and c. independent living. The independent variable would be the demographics of the foster youth in our sample. For this variable the operational definitions would be a. race, b. gender, and c. number of foster placements. 

 

3.     How are you measuring this variable? Describe this/these in detail. Is this an existing instrument or did you create it?

a.      For the level of measurement, for dependent variable it would be nominal and for the independent variable it would be categorical. For our study, attributes cannot be measured in numerical data. In our study the only numerical operation used would be counting. From counting the variables and operational definitions, the researchers would be able to turn the data into percentages for statistical analysis.

 

4.     What are the strengths and limitations of using these measures?

a.      The strengths of these measurements would allow the researchers to describe the differences in the sample elements that are not able to calculate through numbers. This would allow the demographics to be exhausted and exclusive. But a weakness would be that nominal is not it is not ordinal nor mathematically precise.

a.      To what extent does a history of sexual abuse affect the permanency outcomes for foster youths?

b.     Our hypothesis is children placed in the foster care due to sexual abuse will be less successful to achieve permanency compared to children placed in foster care for other maltreatment.

 

2.     What is your sampling strategy? 

a.      The sampling approach to be utilized in this research proposal is cluster sampling. Approximately 300 adolescents (ages 13-17) will comprise the sample population from the localities listed above. The researchers will gather the sample population through the Foster Care Demographic Report of December 2017 as well as the  

 

3.     Identify your research design and provide the action steps that you will use to complete this study.

a.      The research design for this proposal will be a cross-sectional research design, due to the data is collected from the sample at one point in time. The action steps for this study are the following: a) gather a sample (cluster sampling) of foster youth (ages 13-17), b) categorize the sample according to race, gender, and number of previous foster placements (demographics), c) determine how many foster youths in the sample have encountered sexual abuse through Virginia Department of Social Services (VDSS) reports and local foster care agencies, and d) determine if any of the foster youths are in the process of adoption or reunification with birth parents/relatives.

 

4.     Please explain why your research design is appropriate for your question.

a.      Cross-sectional research allows for the researchers for this proposal to collect data from one point in time to analyze the causal effects between variables. This type of research design also allows for increase in feasibility of the study due to the time constraints not serving as a problem within this study. This study will use records gathered from VDSS and local foster care agencies regarding foster youths in various localities of Virginia that will work to make the sample representative. As this data will be retrospective, it will serve to be more reliable concerning past experiences of the participants.

 

5.     What are the strengths and limitations of your design. 

a.      Although the cross-sectional research design is suitable in that the independent variables are fixed and use of retrospective records is permitted, this design does not track causal effects over time, and time order is crucial in determining causal analysis (i.e., what variable changes another variable).