Social Work research methods include surveys, ethnographic descriptions, studies, randomized trials, and needs tests. What makes one data point stronger than another? Ask any researcher, social work domain or otherwise. They’ll refer to the importance of avoiding the many forms of researcher bias, clearly expressing the problem, and using the properly structured methodology, among other essential steps.
Strategies for collecting reliable data may vary slightly depending on the nature of the study, but the underlying concept is this: nothing outside the natural environment can influence the data. If the researcher controls the data, then the correlation between the hypothesis and the results is weakened significantly.
So, how can researchers in the social work field strive for the highest standards of objectivity in their findings? The answer starts with the proper methodology. The structure of each study needs to conform to the environment in which the hypothesis was formed and not the other way around. For example, if a researcher wants to test how participants respond to different management styles in the workplace, they would do best not to remove the person from their work environment – even if the researcher simulated one of their own.
In some scenarios, observing participants in their environments like the above example is appropriate. Maybe a simple survey would indeed work when it comes to perceptions and behaviors that aren’t dependent on the environment. However, researchers in the social work field have to rely on several research methods to observe and collect the data as it exists in its natural domain. Let’s summarize some of the most common structures, starting with the already mentioned survey method.
Especially when researchers have access to large participant groups, surveys are a simple, affordable, and reliable research method. The structure is simple: participants answer a series of questions designed to test the researcher’s hypothesis. If the researcher wants to evaluate the effects of digital media on certain perceptions, for example, they could ask participants to express their thoughts on popular events and people. Then, researchers send out the surveys, aggregate the results and form their conclusions based on the trends within the data.
As with many of the following methods, it is not the implementation of the survey method itself that can be tricky but knowing when and how to use it properly. If the topic(s) being covered by the survey can’t be addressed with simple questions and answers, researchers need to opt for more open-ended data collection techniques. If respondents feel embarrassed or incriminated by answering truthfully, they may skew the results – observational methods would prevent this issue in many cases.
Like a probe sent deep into a planet’s surface to collect data unobtainable from the surface, ethnographic studies seek to immerse the researcher in another culture for more significant insights into any number of behaviors and beliefs. Contrary to surveys, ethnographic methods are generally more time-consuming and costly. A researcher may travel across the world to live within a culture for weeks, months, or longer, adopting that culture’s practices to enrich their understanding. Then, they bring all of their data back home, where they use it to help other groups merge with members of the researched group.
Ethnographic research models can overlap with others. As mentioned, the researcher will generally travel to an area and immerse themselves in the culture. This can include:
- Informant interviews
- Surveys and census data
Popular in the business world, case studies are also well-suited to research efforts in social work. Simply put, a case study is an example – a real-life scenario that provides a testing ground for a hypothesis. Researchers can examine data from an ethnographic study, for example, even if the survey had a completely different objective, to demonstrate certain behaviors’ social or individual impact (or lack thereof). Though everyday events can be justified as case studies, researchers are often hard-pressed to prove that no extraneous variables affect the data since real-life scenarios don’t occur in controlled environments.
Case studies are helpful in many scenarios, but they address a specific theory. Therefore, they can be used throughout the literature review and research phases to accomplish the following objectives:
- Practically demonstrate a theory
- Call for more research
- Debunk a hypothesis
- Test research findings in the real world
- Uncover new variables affecting the hypothesis
Experiments in the medical field especially tend to follow a model that compares the results (of a drug, treatment, etc.) across two groups: the control group, which doesn’t receive treatment, and the experimental group, which does. In a single-system design, however, there is only one group. Often, this “group” is just one person. Moreover, the person or group is generally studied to assess their response to different variables over a long period.
With no control group, though, how do researchers gauge the effects of any particular variable? By manipulating the variable itself, not the audience. Single-system designs test the products of different independent variables. The experimenter applies the dependent variable and the result of these changes, and the theory being tested.
Let’s say that a researcher in the social work domain wants to determine the effect of digital media consumption on antisocial behaviors. Instead of setting up a control group (no digital media consumption) and an experimental group (two hours of digital media consumption per day per participant) to test their hypothesis, the researcher will change the nature of the digital media consumption for a single participant, recording the results of each change.
This particular vein of research is highly relevant to social workers, who often ally with programs of all kinds as a way of increasing access to vital resources for their clientele. The government or private investors may fund a program. Regardless, nobody supports a project unless they think it will be successful. A program evaluation allows everyone to assess a program’s fitness across multiple dynamics.
This research method requires a comprehensive look at recent findings to prove the effectiveness of a particular program. Even after a program has launched, program evaluations can help to refine things for greater efficiency. The following list of questions will help to define the purpose and applications of a program evaluation:
- Will this program work?
- How much will the program cost per participant?
- How can we expand the program?
- Is there a better way to serve the program’s population?
- Are there any disadvantages for program participants?
Needs assessments are also fundamental to the sociological perspective because they seek to identify deficiencies in specific populations. Of course, one does not define a population only by region, income level, or ethnicity. However, these three factors comprise the majority of cases.
This research method is integral to social work at all levels. A social worker in the field, for example, can use needs assessments to identify opportunities for improvement with an individual client. Conversely, researchers, program planners, and executive-level social work professionals can apply needs assessments to entire communities to affect change on a larger scale. In either case, needs assessments are part of the planning process when conducting research, creating resources, or developing a care plan for one person.
Finally, the randomized trial is one of the purest and most broadly applied experimental models. Randomization, in this case, refers to how you select participants to be part of the control or experimental groups. Furthermore, you experiment with a formulaic, easily reproducible, and highly measurable fashion. First, the randomly assigned experimental group is subjected to the variable. It may be a treatment or a specific stimulus. Then, the randomly assigned control group is not. Next, the response of both groups are measured and compared, and when applicable, a new variable is tested in the same fashion.
This research model is most appropriate when responses are easily quantifiable in both social work and the medical field. Comparing subjective responses between two groups yields less actionable and prominent information than, for example, a measurable change in blood pressure.
To reiterate, no research model is objectively “better” than the other; each has its application. Properly selecting and applying a model (or a combination of models) requires researchers to comprehensively evaluate the subject’s environment, the nature of the data (subjective, objective, or both?), the hypothesis, and so forth. Nevertheless, the proper research method can introduce precious findings that hold up against future inquiries when used correctly.