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According to the Science Council, science is defined as “the pursuit and application of knowledge and understanding of the natural and social world following a systematic methodology based on evidence” (http://sciencecouncil.org/about-us/our-definition-of-science). According to Wikipedia, science is “a systematic enterprise that builds and organizes knowledge in the form of testable explanations and propositions about the universe” (https://en.wikipedia.org/wiki/Science). It is not about hunches, or untested opinions, or something you were told.

Science is based on a special method of inquiry that includes clarity of the research question, a systematic method of investigation, the objective collection and analysis of data, and the drawing of conclusions that are logical based on the results of your data analysis. It is not the cherry-picking of facts to support an opinion, nor is it an incomplete inquiry with many critical avenues untouched by the inquiry. Instead, it is open and comprehensive.

Scientific research is a means of gaining relevant knowledge through the use of the scientific methods. The scientific method is orderly and strives for the achievement of objectivity. An inquiry that is designed to prove a point is not an example of research that fits the spirit of scientific inquiry. A study that is incomplete or illogical also fails to meet the standards of the scientific method.

Sometimes our observations from day to day are a good guide for action. Sometimes, however, our observations are in error. A typical error is a failure to see the evidence that contradicts an opinion that we have embraced. The scientific method is designed to reduce human error in observation. It moves in a logical sequence of steps. For example, we must have a clear idea of what we want to find out before we select a method for our inquiry. We should be clear about the nature of our target population before we select people for our study. Before we can draw conclusions about our research question, we must collect and analyze data. If we are abiding by the spirit of scientific inquiry, we will use study methods that provide us with the opportunity to find that our previous expectations about reality are not supported, as well as the opportunity to find support for our expectations.

Research methods can be used to test certain assumptions you have acquired in your work or questions that you have developed. When your perceptions are supported by your research efforts, you can have more confidence in their accuracy, and perhaps, you will learn something in this process that will refine your understanding. When your expectations are not supported by your research results, you can be stimulated to further growth by your efforts to rethink the problem under study. As you continue in this growth and the validation of practice principles and methods, you will be in a better position to meet the challenges of accountability in social work, which have been increasing in recent decades.

The spirit of scientific inquiry suggests certain behaviors. First, you would not state the purpose of your study as proving that your expectation is correct. You do not study the effectiveness of your tutoring program in improving the grades of your clients for the purpose of proving that the program is effective. You conduct it for the purpose of finding out whether it is effective.

Second, your examination of information should be objective and comprehensive. You should not cherry-pick information so that you only consider data that support your expectations and you systematically ignore data that fail to do so.

Third, you follow a logical set of procedures when you conduct scientific research. This means that you do not start the process by deciding on the questions you want to put on the questionnaire. Instead, you start the process by deciding on the purpose of your study.

Fourth, your conclusions should be consistent with the data you analyzed. You should keep your opinions out of the conclusions that you draw from a scientific study. If your data were found not to be statistically significant, then you have data that can be explained by chance, so you cannot take them seriously with regard to the study conclusions. Your statement should say that you failed to find improvement in anxiety in your clients or you failed to find that those who engage in regular aerobic exercise had less stress than others. This may seem counterintuitive, because you did find that scores were higher at the end of treatment than before treatment. But if these differences were not found to be statistically significant, you cannot rely on them to do a good job of predicting what you would find if you repeated this study with another sample of people drawn from the same study population.

Suppose you undertook a study of the relationship between various sources of social support and social functioning (school grades, health behaviors, etc.) for a sample of adolescent mothers. You measured support with regard to four sources: partners, mothers, fathers, and grandmothers. Suppose you found that those with high support from partners had better outcomes. Suppose further that you found the same relationship between support from mothers and outcomes for the adolescent subjects. What should be your conclusions? Should you include the variable of grandmother support as a key element of a service plan for this population? See Figure 1.1 for a graphic display. If you failed to find that grandmother support was related to social functioning for this population, why would you conclude that this be included in a service plan? It does not make sense.

Fifth, the scientist assumes that people sometimes err in making observations. The questionnaire may not accurately measure what it was intended to measure. For this reason, methods are used in science to test the accuracy of a measurement tool. Furthermore, we continue to conduct research on a given theme to see if the results are consistent with what was found previously.

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Figure 1.1 ■ Consistency: What’s Wrong With This Picture?