Jasmine J
RE: Unit 3.1 DB: Quantitative Research Design
Quantitative research is used to test a hypothesis. According to Sheperis et al. (2017), quantitative designs are research designs that collect numerical or categorical data. An example of a hypothetical quantitative research design that includes independent variable (IV), the variable being manipulated, and dependent variable (DV), the variable being studied, this writer would use that would be beneficial in her future work is to test how mental illnesses has impacted a person’s mindset. The IV in this writer’s quantitative research design will be the person’s mindset and the DV will be the mental illness.
People with severe mental illness have difficulties in carrying out daily tasks (Lestari et al., 2020). For several individuals who has been diagnosed with a mental illness has developed or experienced symptoms of low self-esteem, depression, anxiety, hopelessness, fear, loneliness, etc. Many of these individuals lack the support system they need to understand how to manifest through their lives without have negative mindsets as if their life is over due to their diagnosis.
This research design would be strictly for adults ages 18 to 65, totaling about 150 participants who have been hospitalized and diagnosed with a mental illness. This writer would gather feedback from each participant using a survey method by questioning each adult what age they were first diagnosed, what events led to their hospitalizations, the effects mental illness has caused to their lives, and do they see potential in themselves (e.g., obtaining a job, furthering education, relationship, children, etc.). This writer’s purpose is to enhance individuals who are suffering from a mental illness see positivity within themselves and for others to understand how being bias can make a person feel worthless. The goal of every community is to ensure people with severe mental illness live an independent life by as them in dealing with the consequences of mental illness (Lestari et al., 2020).
References:
Lestari, R., Yusuf, A., Hargono, R., Ahsan, A., Setyawan, F. E. B., & Damayanti, N. A. (2020). The impact of social capital, demographic factors, and coping strategies on community adaptation in supporting people with severe mental illness. Journal of Public Health Research, 9(2), 179–182.
Sheperis, C.J., Young, J.S., & Daniels, M. H. (2017). Counseling research: Quantitative, qualitative, and mixed methods (2nd ed.). Pearson Education, Inc.
Ashley M
RE: Unit 3.1 DB: Quantitative Research Design
Quantitative research is a style of research that focuses on quantity, the collection and evaluation of the data collected. It is formed from a reasonable approach where importance is placed on the analysis of theory, influenced by researchers and positivistic viewpoints (Orange & Lastrapes, 2019). Independent variables are the variables that are altered when testing the dependent variables. These are the parts that a researcher will adjust to determine if it has an effect on the dependent variable. Whereas the dependent variable is the variable being evaluated in research that is “dependent” on the independent variable (Orange & Lastrapes, 2019).
In the Writers current field, she feels that one dependent variable that would be most useful to evaluate would be the survivor’s success rates in remaining out of the life. The dependent variable would be the services provided. The utility for this research would be to find out what services are most effective in helping a survivor be successful in remaining out of the life. When speaking of “the life” in terms of CSEC this would mean remaining out of exploitation. The possible limitations to this research it that not all programs work the same for every survivor. This being said what set of programs work great for one person may not work at all for another which is why its so vital to have as many options available as possible.
References
Orange, A., & Lastrapes, R. (2019). Teaching Qualitative Analysis to a Quantitative. The Qualitative Report Conference.
Taylar F
RE: Unit 3.2 DB: Theory Development
Researchers must first determine exactly what they will be researching and identify the independent and dependent variables of the research study. To determine which research design to use, researchers must develop a thorough theory or hypothesis that will allow them to see which method will yield better results/ findings. Sage Pub (2018) explains that the three approaches to research are a mixed methods research, qualitative research, and quantitative research. Mixed methods research utilizes both qualitative and quantitative data, but it’s more beneficial to narrow it down to either qualitative or quantitative. Pyrczak and Tcherni- Buzzeo (2019) explain that qualitative data utilized words while quantitative data is numbers and statistical values.
Sage Pub (2018) argues that if researchers are trying to answer an open-ended hypothesis, such as how having a pet animal improves someone’s mental health, they should use a qualitative approach. However, if researchers are trying to determine the number of individuals in statistical form who have a pet and report improved mental well-being, they should use a quantitative approach. For instance, qualitative research would seek to answer how having a pet affect’s one’s mental health, and quantitative research would examine an exact number of individual’s who have a pet and report improved mental well-being.
Personally, this writer can appreciate a mixed methods approach because it answers both open-ended and closed hypothesis, and determines data expressed in words and numbers. However, if this writer had to pick between the two approaches, she would chose to use a quantitative approach because it is more controlled, allowing for better validity, reliability, and generalizability. Wright et. al (2016) says that quantitative researchers have a better chance of finding reliable and valid results because their approach uses deductive logic and exact data measurements. Additionally, quantitative research findings can be explored to then find further arguments and theories which can improve the generalizability of results (Wright et.al, 2016)
References
Pyrczak, F. & Tcherni-Buzzeo, M. (2019). Evaluating research in academic journals: A practical guide to realistic evaluation (7th ed.). Pyrczak Publishing.
Sage Pub. (2018). The selection of a Research Approach. Sage Publications. Retrieved from https://us.sagepub.com/sites/default/files/upm-binaries/55588_Chapter_1_Sample_Creswell_Research_Design_4e.pdf
Wright, S., O’Brien, B. C., Nimmon, L., Law, M., & Mylopoulos, M. (2016). Research Design Considerations. Journal of Graduate Medical Education, 8(1), 97–98. https://doi.org/10.4300/JGME-D-15-00566.1
Rebecca G
RE: Unit 3.2 DB: Theory Development
Scientists select a research problem for any of several reasons. Some studies are undertaken to evaluate or to advance a particular theory. Others may be undertaken for the purpose of comparing the adequacy of two or more theories. Researchers must first decide precisely what they will be researching and identify the independent and dependent variables of the research study in order to form a hypothesis. The hypothesis should arise sensibly from previous findings or the predictions of a particular theory. One the Researcher has done this they can decide which method of research to follow throw on, that being quantitative, qualitive, or mixed methods (Sheperis, Daniels, & Harry, 2017).
Theories give researchers different “lenses” through which to look at complicated problems and social issues, focusing their attention on different aspects of the data and providing a framework within which to conduct their analysis.
When it comes to data saturation, this is where the information becomes redundant of data already collected (Benjamin Saunders, 2018). When the researcher begins to hear the same comments again and again, data saturation is being reached. It is then time to stop collecting information and to start analyzing what has been collected. Purposeful sampling is a technique widely used in qualitative research for the identification and selection of information-rich cases for the most effective use of limited resources (Lawrence A. Palinkas, 2015). This involves identifying and selecting individuals or groups of individuals that are especially knowledgeable about or experienced with a fact of interest. Generalizability theory is a statistical theory for evaluating the dependability or reliability of behavioral measurements. G theory estimates multiple sources of measurement error and permits decision makers to design a measurement procedure that minimizes error. Generalizability theory (G-theory) is widely recognized as a comprehensive framework for representing score reliability (Walter P. Vispoel, 2017).
This writer would most likely utilize generalizability theory. This writer has used Learning Target Rating Scale (LTRS), it is a measure designed to evaluate the quality of teacher-developed learning targets for embedded instruction for early learning. A G-theory could be used to measurement dependability of LTRS scores.
References
Benjamin Saunders, J. S. (2018). Saturation in qualitative research: exploring its conceptualization and operationalization. Quality and Quantity, 1893–1907.
Lawrence A. Palinkas, S. M. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health, 533–544.
Sheperis, C. J., Daniels, J., & Harry, S. &. (2017). Counseling Research Quantitative, Qualitative, and Mixed Methods. Ney York NY: Pearson Education, Inc.
Walter P. Vispoel, C. A. (2017). Applications of Generalizability Theory and Their Relations to Classical. American Psychological Association, 1-26.
Rebecca G
RE: Unit 3.3 DB: Research Instruments
Research bias happens when the researcher skews the entire process towards a specific research outcome by introducing a systematic error into the sample data (Sheperis, Daniels, & Harry, 2017). In other words, it is a process where the researcher influences the systematic investigation to arrive at certain outcomes. When any form of bias is introduced in research, it takes the investigation off-course and deviates it from its true outcomes.
Data collection is an important step in the research process. The instrument you choose to collect the data will depend on the type of data you plan on collecting qualitative or quantitative and how you plan to collect it (Sheperis, Daniels, & Harry, 2017).
A rating scale is a common method of data collection that is used to gather comparative information about a specific research subject. Specifically, a rating scale is a type of multiple-choice question, and it allows survey respondents to assign a value to a product or service. This writer will be using a rating scale in her work as a LADC called Alcohol Dependence Scale (ADS). The ADS provides a quantitative measure of the severity of alcohol dependence consistent with the concept of the alcohol dependence syndrome. The 25 items cover alcohol withdrawal symptoms, impaired control over drinking, awareness of a compulsion to drink, increased tolerance to alcohol, and salience of drink-seeking behavior (Doyle & Donovan, Journal of studies on alcohol and drugs). Sherpis et. al (2017) states that rating scales differ in observations and can suggest a judgement on behalf of the observer, causing the researcher to form a bias.
Other forms of instruments competed by participants are questionnaires and personality inventories where a bias could be formed. Self-reports are commonly used in psychological studies because they can yield much valuable and diagnostic information to a researcher or a clinician. One of the most commonly used self-report tools is the Minnesota Multiphasic Personality Inventory (MMPI) for personality testing. One of the primary advantages of self-report data is that it can be easy to obtain. It is also an important way that clinicians diagnose their patients by asking questions (Stanborough, 2020). Those making the self-report are usually familiar with filling out questionnaires. Collecting information through a self-report has limitations. People are often biased when they report on their own experiences. For example, many individuals are either consciously or unconsciously influenced by social desirability. That is, they are more likely to report experiences that are considered to be socially acceptable or preferred.
References
Doyle, S. R., & Donovan, D. M. (Journal of studies on alcohol and drugs). A Validation Study of the Alcohol Dependence Scale. 2009: 689–699.
Sheperis, C. J., Daniels, J., & Harry, S. &. (2017). Counseling Research Quantitative, Qualitative, and Mixed Methods. Ney York NY: Pearson Education, Inc.
Stanborough, R. J. (2020). What to Know About the MMPI Test. Retrieved from https://www.healthline.com: https://www.healthline.com/health/mmpi-test#clinic…
Griselda V
RE: Unit 3.3 DB: Research Instruments
Professor and classmates,
The science of research is deeply based on different variables and focus on a specific variable of interest. The key element is taking in consideration the primary objective of the research intent. The following variable quantity should be taking in consideration during the beginning of a research such as the five W’s (what, who, when, where, and who). The science of research is precise and little room left for personal assumptions without a demonstrable data. An approach to take in consideration is utilized research instruments already developed and tailor them to the data being measured. Utilizing sub-areas of the quantitative studies such as attitude scales, self-checklist, and others is a feasible alternative. A changing to take in consideration is subjective results which can occur as the way the information was interpreted by the individual collecting the data. Furthermore, the willingness of partakers, the setting of the study, the most important reason of the research, and the observation and interpretation of data could create a bias result (Sherpis et. al, 2017).
Research bias happens when the researcher angles the entire process towards a specific research outcome by creating a systematic error into the sample data. In other words, it is a process where the researcher influences the systematic investigation to arrive at certain conclusions. When any form of bias is introduced in research, it takes the investigation off-course and deviates it from its true outcomes. Research bias can also happen when the personal preferences and predilections of the researcher have excessive influence on the study. For instance, administering your survey online; thereby limiting it to internet savvy individuals and excluding members of your population without internet access. Another example is collecting data about parenting from a mother’s group. The findings in this type of research will be biased towards mothers while excluding the experiences of the fathers (Sherpis et. al, 2017).
References
Sheperis, C.J., Young, J.S., & Daniels, M. H. (2017). Counseling research: Quantitative, qualitative, and mixed methods (2nd ed.). Pearson Education, Inc.
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