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Data Collection and Analysis

Credible and reliable research studies require meticulous research study design and conduction. One of the major areas for consideration for successful research conduction is data collection and analysis. Proper data collection and analysis involve formulating the main research question and its related questions to determine the answer to the main research question. This assignment identifies how a sample research study may be conducted. This assignment starts by stating the main research question and the area of focus of the related questions. The paper then identifies the kinds of data required to answer the questions, the respondents of the study, and methods of data collection and analysis. This paper concluded by describing the intended audience for the study’s results and the most appropriate method of results presentation.

Main Research Question and Critical Sub-Questions

The main research question is ‘What are the mental healthcare outcomes in sexual abuse victims?’ Sexual abuse results in lasting mental and physical impacts on its victims. Consequently, it is vital to design effective corrective measures to determine the extent of the cognitive effects on abuse victims. Sub-questions are necessary to effectively answer and address all possible areas of the leading research question (Bordens & Abbott, 2011). The critical sub-questions for the main research question include: Age when the abuse took place? The frequency of sexual abuse? Relationship between victim and perpetrator of abuse? Accessibility to mental health care services post abuse? Socioeconomic conditions of victims? Victim’s opinion on legal justice accorded due to the crime?

These sub-questions address factors are likely to impact mental healthcare when coupled with sexual abuse. Addressing all the questions may result in determining factors that exacerbate mental health problems among sex abuse victims (Zohrabi, 2013). Consequently, researchers and policymakers may develop strategies to improve the mental health of the victims.

Pool of Participants

The subject of sexual abuse and mental health cuts across all demographics in the population. Sexual abuse victims exist amongst all socioeconomic groups, genders, age groups, and ethnic groups. Consequently, the pool of participants in the study will be determined from the entire population. Mental health victims from the whole population will be eligible participants in the study.

The research team will use a random sampling technique to select the respondents for the study. Random sampling gives every member of the population an equal probability of being selected to participate in the survey (Bordens & Abbott, 2011). Consequently, the study can generate results and findings of high accuracy; with minimum biases and high internal validity.

Data Collection Methods and Tools

Both qualitative and quantitative data are necessary to answer the main research question and its sub-questions. Therefore, the data collection procedure will involve a mixed-methods research design, both qualitative and quantitative research design. The data collected from the research will be in numbers and words. Qualitative data aids in developing in-depth analysis and results of a given research question (Moser & Korstjens, 2017). Quantitative data allows generalized numerical data collection to determine the relationship between variables, aiding policy formulation (Rutberg & Bouikidi, 2018). Applying both qualitative and quantitative methods ensures that the limitations of the methods are minimized and their benefits optimized. Combination of both qualitative and quantitative data collection results in highly in-depth and objective results.

Qualitative data involves a non-numerical approach where researchers collect data about the opinions, motivations, and characteristics of research participants. The nature of the research question on mental healthcare in sexual abuse victims necessitates collecting qualitative data. Qualitative data collection is essential in answering the research question as it provides a more meaningful and in-depth perspective on the opinions of individual abuse victims.

Quantitative data collection will be used to determine numerical data essential in answering the research question. Numerical data obtained through quantitative data collection is vital to deciding relationships such as; how the frequency of abuse impacts mental wellness, the relationship between mental health wellness and the age of victims at the time of the abuse, and the relationship between mental health state and the time passed after abuse. Analysis of quantitative data will be used to determine the correlation between mental health wellness and the various research variables (Bloomfield & Fisher, 2019). Data collection through quantitative methods results in statistical data less likely to be subjective.

Data collection tools for use in the study will include interviews and questionnaires. In-person interviews conducted by the researchers will aid in collecting personal data of the respondents; regarding their sexual abuse and mental health wellness. Variables that will be assessed in the interviews will include; opinion on garnered justice, socioeconomic condition, relationship with the perpetrator, and accessibility to mental health counselling post abuse. Interviews may also be used to determine the respondents’ objectivity, to enable sieving out biased responses. The questionnaire will offer generalised sub-questions and questions requiring numerical answers (Hangel & Schickore, 2017). Variables addressed in the questionnaire will include; age at abuse, number of years past after abuse, and frequency of abuse. The questionnaire will involve open-ended and multiple-choice closed-ended questions (Moser & Korstjens, 2017). The research design will include answering the questionnaire first, then being undertaken through the interview.

Interviewing and questionnaires will be coupled with secondary data collection to glean the information obtained through data collection. Secondary sources will provide additional information to assess the validity and usefulness of the collected data. Literature from past research studies on various demographics will be used to determine the validity of findings from the data collection procedure (Hangel & Schickore, 2017). The literature review helps determine whether factors found in the study align with the results of other studies on the association of mental health in sexual abuse victims. Gleaning the conclusions of the data collection procedure through literature will be used to determine whether there is causation, in addition to correlation, between the dependent and independent variables in the study.

Data Analysis

Analysis methods will involve analysis of both quantitative and qualitative data. Accurate and dependable analysis methods are essential to translate collected data into usable results and findings. Qualitative data will be analyzed through coding. Coding enables the organization and labelling of data to identify relationships between the variables (Rutberg & Bouikidi, 2018). Coding allows a more straightforward interpretation of responses and a summary of the entire data collection process. One of the coding methods that I will use in the analysis is the thematic analysis coding method. The thematic analysis enables data unification with similar thematic patterns (Hangel & Schickore, 2017). Responses from the interview processes and the questionnaires will be grouped to determine general trends in the respondents’ perceptions.

The coding of the data will encompass the use of automatic coding. Automatic coding comprises thematic analysis software through natural language processing, artificial intelligence, and machine learning, which are valuable tools to break up collected data into themes. Automatic coding saves time by simplifying the coding process. The researchers can kick start the coding process without training the algorithms or setting up categories and themes in advance. An added benefit of automatic coding is that it can identify themes and unknowns that would have been overlooked through manual coding (Hangel & Schickore, 2017). Automated analysis is also able to unify data from various research studies.

Quantitative data will be analyzed through statistical tools to determine relationships between the variables. Binary logistic regression will identify the variables’ prevalence and association (Bloomfield & Fisher, 2019). The research will encompass the use of frequency distribution tables to determine frequencies of numerical variables such as; frequency of abuse, ages of victims at the time of the abuse, period passed since abuse and frequency of mental health issues in the victims.

Qualitative data analysis will involve a description of the data through descriptive and inferential statistics (Hayes, 2020). Data on demographic and mental health characteristics will be displayed in tabular form to determine the frequency among the respondents. Statistical Product and Service Solutions (SPSS) will determine correlations and their significance levels between variables (Hayes, 2020). The SPSS tool is beneficial in predicting how variables in the study design influence each other. Consequently, it is possible to determine which characteristics exacerbate mental health issues.

Results Presentation and Relevant Audience

The results of this study will shed light on characteristics that influence mental health in victims of sexual abuse. Consequently, the study findings benefit various public agencies, policymakers, social workers, psychologists, scholars, and victims of sexual abuse. Social workers and psychologists may use the results of this study to determine necessary interventions for improving the mental wellness of victims of sexual abuse. Policymakers may use the information from the survey to legislate better policies for improving the mental health of the victims (Bordens & Abbott, 2011). The study findings benefit scholars from multiple professionals to shed more light on factors that affect mental wellness. The study’s conclusions may be built upon to conduct more research on the welfare of victims of sexual abuse, determine more characteristics that influence mental health wellness, and design effective intervention strategies.

The study findings will be presented to the audience through publication in a reputable social work journal and a public presentation. The public exhibition will allow launching the research and explaining its contents to relevant authorities and parties. The bodies in the display may use the findings to improve the welfare of victims of sexual abuse. The research study will be published in a reputable journal to guarantee its global access to users (Hangel & Schickore, 2017). The findings will provide a starting point for other studies and be used to guide policies in various localities.

In conclusion, proper design is necessary to conduct research that will result in valid and reliable findings. Mixed methods research may be used to optimize the benefits of both quantitative and qualitative data collection and analysis methods. Qualitative data is analyzed through coding to group responses with similar themes. Statistical methods and tools are used in analyzing quantitative data. Any study’s results should be compared with the findings of similar studies to determine the study’s external validity. In the above analysis, the chosen methods of presentation of results are public presentation and publication in a reputable journal. These presentation methods enable access of information to various audiences. These audiences can use the findings to formulate policies and design interventions for improving the welfare of victims of sexual abuse.


Bloomfield, J., & Fisher, M. J., (2019). Quantitative Research Design. Journal of the Australasian Rehabilitation Nurses Association 22 (2), 27-30.

Bordens, K. S., & Abbott, B. B., (2011). Research Design and Methods: A Process Approach, 8th Ed. New York: McGraw Hill.

Hangel, N., & Schickore, J., (2017). Scientist’s Conceptions of Good Research Practice. Perspectives on Science 25(6), pp. 766-791.

Hayes, A. F., (2020). Statistical Methods for Communication Science. Routledge: New Jersey.

Moser, A., & Korstjens, I., (2017). Series: Practical Guidance to Qualitative Research. European Journal of General Practice 23 (1), pp. 271-273. Doi:

Rutberg, S., & Bouikidi, C. D., (2018). Focusing on the Fundamentals: A Simplistic Differentiation between Qualitative and Quantitative Research. Nephrology Nursing Journal 45 (2), pp. 209-213.

Zohrabi, M., (2013). Mixed Method Research: Instruments, Validity, Reliability, and Reporting Findings. Theory and Practice in Language Studies, 3 (2), pp. 254-262.


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