Data and Methods Research Paper Sample

Data Collection and Research Design

The proposed study will seek to collect data from a significantly large population, comprising of 1200 participants that are above 18 years and have experienced sexual assault at some point in their life. These will be recruited from diverse sources including support groups, sexual assault survivor platforms and community centers. To ensure representativeness and diversity, the participants will be recruited from as many groups as possible. Furthermore, the recruitment process will be conducted across different locations within four states (Michigan, Illinois, Massachusetts and Alaska), thereby incorporating participants from diverse social classes, genders, religious affiliations and races.

The collection of data will adopt a mixed-methods approach, in which both qualitative and quantitative data will be gathered. Upon giving consent, all the participants will be required to complete an online questionnaire. This tool will capture their demographic information, sexual assault experiences and mental health status. To enrich the study, a random sample of 100 participants will be selected for in-depth interviews. As noted by Curry, Nembhar and Bradley (2009), in-depth interviews in mixed methods are critical in provision of richer qualitative insights. The interviews will last about 45 minutes to ensure that adequate data is obtained from each of the interviewees. For the questionnaires, participants will require about one hour to fill it.

The generalizability of the data to the general population is not feasible. However, it can be generalized to groups and populations of sexual assault victims. Furthermore, the diversity of the sample will be critical to the generalizability of the findings. The lack of generalizability to the general population is one of the major disadvantages of this data collection approach. The other hiccup is that data on sexual assault is very sensitive hence; its acquisition is a tall order. That notwithstanding, this research design provides an opportunity for the researcher to comprehensively underscore the relationship between sexual assault and mental health.

Methods

Hypothesis: Sexual assault victims exhibit high levels of mental health conditions.

The study will have three different types of variables; the independent variable, the dependent variable and the control variables. The independent variable is ‘the experience of sexual assault’ whereas the dependent variable is mental health conditions such as depression, PTSD and anxiety. The control variables are social class, race, gender, anger scale, victimization and religiosity.

Operationalization strategy of the study will involve self-disclosure by the participants through the questionnaires. The status of mental health will also be through self-disclosure for all the participants. However, for the 100 participants that will be interviewed, mental health variables will be measured using standardized clinical assessments and psychological assessment tools. For the control variables, they will be assessed based on the demographic data from the questionnaires.

The study will obtain both qualitative and quantitative data, which shall require careful analysis to demonstrate the relationship between sexual assault and mental health. The statistical approach for analyzing the quantitative data will be regression analysis. This is ideal considering that the survey involves only one independent variable. Through regression analysis, the data can point to the relationship between sexual assault and mental health conditions. An analysis of the control variable is also vital as it can point to confounding factors (Kahlert et al., 2017). The qualitative data from the interviews will be analyzed thematically to ensure the researcher understands in good detail, the lived experiences of the victims of sexual assault.

References

Curry, L. A., Nembhard, I. M., & Bradley, E. H. (2009). Qualitative and mixed methods provide unique contributions to outcomes research. Circulation, 119(10), 1442-1452

Kahlert, J., Gribsholt, S. B., Gammelager, H., Dekkers, O. M., & Luta, G. (2017). Control of confounding in the analysis phase–an overview for clinicians. Clinical Epidemiology, 195-204