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A focus on the Statistical Methods Used in Counselling Research
The clinician’s guide to evidence based practice is a guide for clinicians on conducting research authored by Koocher and Hogan (2008). The guide is meant to help practitioners in the field of addiction and psychology to access, interpret, and apply evidence based practices in their profession. The authors came up with this guideline after realizing the necessity of integrating the expertise of the clinicians and the current evidence based research in the context of the specific client. They are of the opinion that practitioners should base their practices on the best available evidence. However, most of the available studies seem to be either too overwhelming, inaccessible or too large to be used as guide in clinical practice. For many years, health practitioners seem to have no time in finding the right research, insufficient skills to retrieve the research and decreased capacity to understanding novel studies. It is therefore with this reason why the guide was designed in order to overcome such challenges. The subsequent part is an overview of the statistical concepts suggested in the article and how they can be applied in counseling research and program based evaluations.
Meta analysis is a statistical term used to refer to a technique of combining and contrasting findings from various studies. The technique is also used to identify the prevalent patterns existing research findings, sources of differences among such findings or the correlation existing among them. In most cases, Meta analyzes are employed in procedures involving systematic reviews. For example, Meta analyses are often used in clinical trials to gain an enhanced understanding on the efficiency of a particular treatment (Greenland and Rourke 2008).
With regard to counseling research and program evaluations, Meta analysis could be very helpful as it offers relevant data in these fields through synthesizing systematic studies and outcomes done by other researchers. This can then turn into effective counseling practices and programs when applied. It is the duty of researchers to ensure that the studies used when conducting meta- analysis are of top quality to guarantee quality practices.
Hypothesis testing is a statistical term used to refer to a technique of establishing decisions based on a scientific research. Hypothesis tests are employed in determining how the anticipated outcome could result into a rejection of the null hypothesis for a particular type of significance. In studies pertaining to counseling and program evaluation, it helps in determining whether the results obtained from a particular study presents new findings that are different from the common wisdom, owing to the fact that the common wisdom are employed in forming such hypothesis (Schervish, 2006). Studies relating to program evaluation and counseling would have to use hypothesis to establish a correlation between two variables. The ethical concern in this method is that researchers are not expected to over -rely on the null hypothesis when conducting their research. In addition, the researchers are also required not to ignore the assumptions made.
Query Formulation Using PICO
Pico is a prefix used in clinical, counseling and program evaluations studies to aid the formulation of correct research questions. The technique is based on the idea that right questions in clinical and counsilling research should or ought to incorporate four parts, namely: patient or population problem, intervention, comparison and finally, the outcome. Forming the right questions to guide clinical and counseling research is a skill that requires thorough knowledge and is essential for the decision making process of the evidence-based practices. In addition to incorporating the PICO components, it is also crucial for the researcher or the author to clarify the type of queries they are going to address and the research technique to the participants. The category of questions to be applied includes Diagnosis, etiology, therapy/prevention and prognosis.