why is quantitative research important in social work

Social Work Research Methods That Drive the Practice

Social workers advocate for the well-being of individuals, families and communities. But how do social workers know what interventions are needed to help an individual? How do they assess whether a treatment plan is working? What do social workers use to write evidence-based policy?

Social work involves research-informed practice and practice-informed research. At every level, social workers need to know objective facts about the populations they serve, the efficacy of their interventions and the likelihood that their policies will improve lives. A variety of social work research methods make that possible.

Data-Driven Work

Data is a collection of facts used for reference and analysis. In a field as broad as social work, data comes in many forms.

Quantitative vs. Qualitative

As with any research, social work research involves both quantitative and qualitative studies.

Quantitative Research

Answers to questions like these can help social workers know about the populations they serve — or hope to serve in the future.

• How many students currently receive reduced-price school lunches in the local school district?
• How many hours per week does a specific individual consume digital media?
• How frequently did community members access a specific medical service last year?

Quantitative data — facts that can be measured and expressed numerically — are crucial for social work.

Quantitative research has advantages for social scientists. Such research can be more generalizable to large populations, as it uses specific sampling methods and lends itself to large datasets. It can provide important descriptive statistics about a specific population. Furthermore, by operationalizing variables, it can help social workers easily compare similar datasets with one another.

Qualitative Research

Qualitative data — facts that cannot be measured or expressed in terms of mere numbers or counts — offer rich insights into individuals, groups and societies. It can be collected via interviews and observations.

• What attitudes do students have toward the reduced-price school lunch program?
• What strategies do individuals use to moderate their weekly digital media consumption?
• What factors made community members more or less likely to access a specific medical service last year?

Qualitative research can thereby provide a textured view of social contexts and systems that may not have been possible with quantitative methods. Plus, it may even suggest new lines of inquiry for social work research.

Mixed Methods Research

Combining quantitative and qualitative methods into a single study is known as mixed methods research. This form of research has gained popularity in the study of social sciences, according to a 2019 report in the academic journal Theory and Society. Since quantitative and qualitative methods answer different questions, merging them into a single study can balance the limitations of each and potentially produce more in-depth findings.

However, mixed methods research is not without its drawbacks. Combining research methods increases the complexity of a study and generally requires a higher level of expertise to collect, analyze and interpret the data. It also requires a greater level of effort, time and often money.

The Importance of Research Design

Data-driven practice plays an essential role in social work. Unlike philanthropists and altruistic volunteers, social workers are obligated to operate from a scientific knowledge base.

To know whether their programs are effective, social workers must conduct research to determine results, aggregate those results into comprehensible data, analyze and interpret their findings, and use evidence to justify next steps.

Employing the proper design ensures that any evidence obtained during research enables social workers to reliably answer their research questions.

Research Methods in Social Work

The various social work research methods have specific benefits and limitations determined by context. Common research methods include surveys, program evaluations, needs assessments, randomized controlled trials, descriptive studies and single-system designs.

Surveys involve a hypothesis and a series of questions in order to test that hypothesis. Social work researchers will send out a survey, receive responses, aggregate the results, analyze the data, and form conclusions based on trends.

Surveys are one of the most common research methods social workers use — and for good reason. They tend to be relatively simple and are usually affordable. However, surveys generally require large participant groups, and self-reports from survey respondents are not always reliable.

Program Evaluations

Social workers ally with all sorts of programs: after-school programs, government initiatives, nonprofit projects and private programs, for example.

Crucially, social workers must evaluate a program’s effectiveness in order to determine whether the program is meeting its goals and what improvements can be made to better serve the program’s target population.

Evidence-based programming helps everyone save money and time, and comparing programs with one another can help social workers make decisions about how to structure new initiatives. Evaluating programs becomes complicated, however, when programs have multiple goal metrics, some of which may be vague or difficult to assess (e.g., “we aim to promote the well-being of our community”).

Needs Assessments

Social workers use needs assessments to identify services and necessities that a population lacks access to.

Common social work populations that researchers may perform needs assessments on include:

• People in a specific income group
• Everyone in a specific geographic region
• A specific ethnic group
• People in a specific age group

In the field, a social worker may use a combination of methods (e.g., surveys and descriptive studies) to learn more about a specific population or program. Social workers look for gaps between the actual context and a population’s or individual’s “wants” or desires.

For example, a social worker could conduct a needs assessment with an individual with cancer trying to navigate the complex medical-industrial system. The social worker may ask the client questions about the number of hours they spend scheduling doctor’s appointments, commuting and managing their many medications. After learning more about the specific client needs, the social worker can identify opportunities for improvements in an updated care plan.

In policy and program development, social workers conduct needs assessments to determine where and how to effect change on a much larger scale. Integral to social work at all levels, needs assessments reveal crucial information about a population’s needs to researchers, policymakers and other stakeholders. Needs assessments may fall short, however, in revealing the root causes of those needs (e.g., structural racism).

Randomized Controlled Trials

Randomized controlled trials are studies in which a randomly selected group is subjected to a variable (e.g., a specific stimulus or treatment) and a control group is not. Social workers then measure and compare the results of the randomized group with the control group in order to glean insights about the effectiveness of a particular intervention or treatment.

Randomized controlled trials are easily reproducible and highly measurable. They’re useful when results are easily quantifiable. However, this method is less helpful when results are not easily quantifiable (i.e., when rich data such as narratives and on-the-ground observations are needed).

Descriptive Studies

Descriptive studies immerse the researcher in another context or culture to study specific participant practices or ways of living. Descriptive studies, including descriptive ethnographic studies, may overlap with and include other research methods:

• Informant interviews
• Census data
• Observation

By using descriptive studies, researchers may glean a richer, deeper understanding of a nuanced culture or group on-site. The main limitations of this research method are that it tends to be time-consuming and expensive.

Single-System Designs

Unlike most medical studies, which involve testing a drug or treatment on two groups — an experimental group that receives the drug/treatment and a control group that does not — single-system designs allow researchers to study just one group (e.g., an individual or family).

Single-system designs typically entail studying a single group over a long period of time and may involve assessing the group’s response to multiple variables.

For example, consider a study on how media consumption affects a person’s mood. One way to test a hypothesis that consuming media correlates with low mood would be to observe two groups: a control group (no media) and an experimental group (two hours of media per day). When employing a single-system design, however, researchers would observe a single participant as they watch two hours of media per day for one week and then four hours per day of media the next week.

These designs allow researchers to test multiple variables over a longer period of time. However, similar to descriptive studies, single-system designs can be fairly time-consuming and costly.

Learn More About Social Work Research Methods

Social workers have the opportunity to improve the social environment by advocating for the vulnerable — including children, older adults and people with disabilities — and facilitating and developing resources and programs.

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Quantitative Research in the Social Sciences

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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numberic and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

• The data is usually gathered using structured research instruments.
• The results are based on larger sample sizes that are representative of the population.
• The research study can usually be replicated or repeated, given its high reliability.
• Researcher has a clearly defined research question to which objective answers are sought.
• All aspects of the study are carefully designed before data is collected.
• Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
• Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
• Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

  Things to keep in mind when reporting the results of a study using quantiative methods :

• Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
• Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
• Explain the techniques you used to "clean" your data set.
• Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
• Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
• When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
• Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
• Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
• Always tell the reader what to look for in tables and figures .

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing datat does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods . Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Designs for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

• Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
• Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
• Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

• Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
• Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
• Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

• Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

• Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
• Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
• Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
• Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

• Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
• Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
• Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine.  An Overview of Quantitative Research in Compostion and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); A Strategy for Writing Up Research Results . The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

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In This Article Expand or collapse the "in this article" section Social Work Research Methods

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• History of Social Work Research Methods
• Feasibility Issues Influencing the Research Process
• Measurement Methods
• Existing Scales
• Group Experimental and Quasi-Experimental Designs for Evaluating Outcome
• Single-System Designs for Evaluating Outcome
• Program Evaluation
• Surveys and Sampling
• Introductory Statistics Texts
• Advanced Aspects of Inferential Statistics
• Qualitative Research Methods
• Qualitative Data Analysis
• Historical Research Methods
• Meta-Analysis and Systematic Reviews
• Research Ethics
• Culturally Competent Research Methods
• Teaching Social Work Research Methods

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Social Work Research Methods by Allen Rubin LAST REVIEWED: 14 December 2009 LAST MODIFIED: 14 December 2009 DOI: 10.1093/obo/9780195389678-0008

Social work research means conducting an investigation in accordance with the scientific method. The aim of social work research is to build the social work knowledge base in order to solve practical problems in social work practice or social policy. Investigating phenomena in accordance with the scientific method requires maximal adherence to empirical principles, such as basing conclusions on observations that have been gathered in a systematic, comprehensive, and objective fashion. The resources in this entry discuss how to do that as well as how to utilize and teach research methods in social work. Other professions and disciplines commonly produce applied research that can guide social policy or social work practice. Yet no commonly accepted distinction exists at this time between social work research methods and research methods in allied fields relevant to social work. Consequently useful references pertaining to research methods in allied fields that can be applied to social work research are included in this entry.

This section includes basic textbooks that are used in courses on social work research methods. Considerable variation exists between textbooks on the broad topic of social work research methods. Some are comprehensive and delve into topics deeply and at a more advanced level than others. That variation is due in part to the different needs of instructors at the undergraduate and graduate levels of social work education. Most instructors at the undergraduate level prefer shorter and relatively simplified texts; however, some instructors teaching introductory master’s courses on research prefer such texts too. The texts in this section that might best fit their preferences are by Yegidis and Weinbach 2009 and Rubin and Babbie 2007 . The remaining books might fit the needs of instructors at both levels who prefer a more comprehensive and deeper coverage of research methods. Among them Rubin and Babbie 2008 is perhaps the most extensive and is often used at the doctoral level as well as the master’s and undergraduate levels. Also extensive are Drake and Jonson-Reid 2007 , Grinnell and Unrau 2007 , Kreuger and Neuman 2006 , and Thyer 2001 . What distinguishes Drake and Jonson-Reid 2007 is its heavy inclusion of statistical and Statistical Package for the Social Sciences (SPSS) content integrated with each chapter. Grinnell and Unrau 2007 and Thyer 2001 are unique in that they are edited volumes with different authors for each chapter. Kreuger and Neuman 2006 takes Neuman’s social sciences research text and adapts it to social work. The Practitioner’s Guide to Using Research for Evidence-based Practice ( Rubin 2007 ) emphasizes the critical appraisal of research, covering basic research methods content in a relatively simplified format for instructors who want to teach research methods as part of the evidence-based practice process instead of with the aim of teaching students how to produce research.

Drake, Brett, and Melissa Jonson-Reid. 2007. Social work research methods: From conceptualization to dissemination . Boston: Allyn and Bacon.

This introductory text is distinguished by its use of many evidence-based practice examples and its heavy coverage of statistical and computer analysis of data.

Grinnell, Richard M., and Yvonne A. Unrau, eds. 2007. Social work research and evaluation: Quantitative and qualitative approaches . 8th ed. New York: Oxford Univ. Press.

Contains chapters written by different authors, each focusing on a comprehensive range of social work research topics.

Kreuger, Larry W., and W. Lawrence Neuman. 2006. Social work research methods: Qualitative and quantitative applications . Boston: Pearson, Allyn, and Bacon.

An adaptation to social work of Neuman's social sciences research methods text. Its framework emphasizes comparing quantitative and qualitative approaches. Despite its title, quantitative methods receive more attention than qualitative methods, although it does contain considerable qualitative content.

Rubin, Allen. 2007. Practitioner’s guide to using research for evidence-based practice . Hoboken, NJ: Wiley.

This text focuses on understanding quantitative and qualitative research methods and designs for the purpose of appraising research as part of the evidence-based practice process. It also includes chapters on instruments for assessment and monitoring practice outcomes. It can be used at the graduate or undergraduate level.

Rubin, Allen, and Earl R. Babbie. 2007. Essential research methods for social work . Belmont, CA: Thomson Brooks Cole.

This is a shorter and less advanced version of Rubin and Babbie 2008 . It can be used for research methods courses at the undergraduate or master's levels of social work education.

Rubin, Allen, and Earl R. Babbie. Research Methods for Social Work . 6th ed. Belmont, CA: Thomson Brooks Cole, 2008.

This comprehensive text focuses on producing quantitative and qualitative research as well as utilizing such research as part of the evidence-based practice process. It is widely used for teaching research methods courses at the undergraduate, master’s, and doctoral levels of social work education.

Thyer, Bruce A., ed. 2001 The handbook of social work research methods . Thousand Oaks, CA: Sage.

This comprehensive compendium includes twenty-nine chapters written by esteemed leaders in social work research. It covers quantitative and qualitative methods as well as general issues.

Yegidis, Bonnie L., and Robert W. Weinbach. 2009. Research methods for social workers . 6th ed. Boston: Allyn and Bacon.

This introductory paperback text covers a broad range of social work research methods and does so in a briefer fashion than most lengthier, hardcover introductory research methods texts.

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A Quick Guide to Quantitative Research in the Social Sciences

(12 reviews)

Christine Davies, Carmarthen, Wales

Copyright Year: 2020

Last Update: 2021

Publisher: University of Wales Trinity Saint David

Language: English

Formats Available

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Learn more about reviews.

Reviewed by Jennifer Taylor, Assistant Professor, Texas A&M University-Corpus Christi on 4/18/24

This resource is a quick guide to quantitative research in the social sciences and not a comprehensive resource. It provides a VERY general overview of quantitative research but offers a good starting place for students new to research. It... read more

Comprehensiveness rating: 4 see less

This resource is a quick guide to quantitative research in the social sciences and not a comprehensive resource. It provides a VERY general overview of quantitative research but offers a good starting place for students new to research. It offers links and references to additional resources that are more comprehensive in nature.

Content Accuracy rating: 4

The content is relatively accurate. The measurement scale section is very sparse. Not all types of research designs or statistical methods are included, but it is a guide, so details are meant to be limited.

Relevance/Longevity rating: 4

The examples were interesting and appropriate. The content is up to date and will be useful for several years.

Clarity rating: 5

The text was clearly written. Tables and figures are not referenced in the text, which would have been nice.

Consistency rating: 5

The framework is consistent across chapters with terminology clearly highlighted and defined.

Modularity rating: 5

The chapters are subdivided into section that can be divided and assigned as reading in a course. Most chapters are brief and concise, unless elaboration is necessary, such as with the data analysis chapter. Again, this is a guide and not a comprehensive text, so sections are shorter and don't always include every subtopic that may be considered.

Organization/Structure/Flow rating: 5

The guide is well organized. I appreciate that the topics are presented in a logical and clear manner. The topics are provided in an order consistent with traditional research methods.

Interface rating: 5

The interface was easy to use and navigate. The images were clear and easy to read.

Grammatical Errors rating: 5

I did not notice any grammatical errors.

Cultural Relevance rating: 5

The materials are not culturally insensitive or offensive in any way.

I teach a Marketing Research course to undergraduates. I would consider using some of the chapters or topics included, especially the overview of the research designs and the analysis of data section.

Reviewed by Tiffany Kindratt, Assistant Professor, University of Texas at Arlington on 3/9/24

The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers... read more

Comprehensiveness rating: 3 see less

The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers references to other resources that can be used to deepen the knowledge. The text does not include a glossary or index. The references in the figures for each chapter are not included in the reference section. It would be helpful to include those.

Overall, the text is accurate. For example, Figure 1 on page 6 provides a clear overview of the research process. It includes general definitions of primary and secondary research. It would be helpful to include more details to explain some of the examples before they are presented. For instance, the example on page 5 was unclear how it pertains to the literature review section.

In general, the text is relevant and up-to-date. The text includes many inferences of moving from qualitative to quantitative analysis. This was surprising to me as a quantitative researcher. The author mentions that moving from a qualitative to quantitative approach should only be done when needed. As a predominantly quantitative researcher, I would not advice those interested in transitioning to using a qualitative approach that qualitative research would enhance their research—not something that should only be done if you have to.

Clarity rating: 4

The text is written in a clear manner. It would be helpful to the reader if there was a description of the tables and figures in the text before they are presented.

Consistency rating: 4

The framework for each chapter and terminology used are consistent.

Modularity rating: 4

The text is clearly divided into sections within each chapter. Overall, the chapters are a similar brief length except for the chapter on data analysis, which is much more comprehensive than others.

Organization/Structure/Flow rating: 4

The topics in the text are presented in a clear and logical order. The order of the text follows the conventional research methodology in social sciences.

I did not encounter any interface issues when reviewing this text. All links worked and there were no distortions of the images or charts that may confuse the reader.

Grammatical Errors rating: 3

There are some grammatical/typographical errors throughout. Of note, for Section 5 in the table of contents. “The” should be capitalized to start the title. In the title for Table 3, the “t” in typical should be capitalized.

Cultural Relevance rating: 4

The examples are culturally relevant. The text is geared towards learners in the UK, but examples are relevant for use in other countries (i.e., United States). I did not see any examples that may be considered culturally insensitive or offensive in any way.

I teach a course on research methods in a Bachelor of Science in Public Health program. I would consider using some of the text, particularly in the analysis chapter to supplement the current textbook in the future.

Reviewed by Finn Bell, Assistant Professor, University of Michigan, Dearborn on 1/3/24

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary. read more

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary.

Content Accuracy rating: 5

As far as I can tell, the text is accurate, error-free and unbiased.

Relevance/Longevity rating: 5

This text is up-to-date, and given the content, unlikely to become obsolete any time soon.

The text is very clear and accessible.

The text is internally consistent.

Given how short the text is, it seems unnecessary to divide it into smaller readings, nonetheless, it is clearly labelled such that an instructor could do so.

The text is well-organized and brings readers through basic quantitative methods in a logical, clear fashion.

Easy to navigate. Only one table that is split between pages, but not in a way that is confusing.

There were no noticeable grammatical errors.

The examples in this book don't give enough information to rate this effectively.

This text is truly a very quick guide at only 26 double-spaced pages. Nonetheless, Davies packs a lot of information on the basics of quantitative research methods into this text, in an engaging way with many examples of the concepts presented. This guide is more of a brief how-to that takes readers as far as how to select statistical tests. While it would be impossible to fully learn quantitative research from such a short text, of course, this resource provides a great introduction, overview, and refresher for program evaluation courses.

Reviewed by Shari Fedorowicz, Adjunct Professor, Bridgewater State University on 12/16/22

The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing... read more

Comprehensiveness rating: 5 see less

The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing the reader with the ability to distinguish two terms that frequently get confused. In addition, links and outside resources are provided to deepen the understanding as an option for the reader. The use of these links, coupled with diagrams and examples make this text comprehensive.

The content is mostly accurate. Given that it is a quick guide, the author chose a good selection of which types of research designs to include. However, some are not provided. For example, correlational or cross-correlational research is omitted and is not discussed in Section 3, but is used as a statistical example in the last section.

Examples utilized were appropriate and associated with terms adding value to the learning. The tables that included differentiation between types of statistical tests along with a parametric/nonparametric table were useful and relevant.

The purpose to the text and how to use this guide book is stated clearly and is established up front. The author is also very clear regarding the skill level of the user. Adding to the clarity are the tables with terms, definitions, and examples to help the reader unpack the concepts. The content related to the terms was succinct, direct, and clear. Many times examples or figures were used to supplement the narrative.

The text is consistent throughout from contents to references. Within each section of the text, the introductory paragraph under each section provides a clear understanding regarding what will be discussed in each section. The layout is consistent for each section and easy to follow.

The contents are visible and address each section of the text. A total of seven sections, including a reference section, is in the contents. Each section is outlined by what will be discussed in the contents. In addition, within each section, a heading is provided to direct the reader to the subtopic under each section.

The text is well-organized and segues appropriately. I would have liked to have seen an introductory section giving a narrative overview of what is in each section. This would provide the reader with the ability to get a preliminary glimpse into each upcoming sections and topics that are covered.

The book was easy to navigate and well-organized. Examples are presented in one color, links in another and last, figures and tables. The visuals supplemented the reading and placed appropriately. This provides an opportunity for the reader to unpack the reading by use of visuals and examples.

No significant grammatical errors.

The text is not offensive or culturally insensitive. Examples were inclusive of various races, ethnicities, and backgrounds.

This quick guide is a beneficial text to assist in unpacking the learning related to quantitative statistics. I would use this book to complement my instruction and lessons, or use this book as a main text with supplemental statistical problems and formulas. References to statistical programs were appropriate and were useful. The text did exactly what was stated up front in that it is a direct guide to quantitative statistics. It is well-written and to the point with content areas easy to locate by topic.

Reviewed by Sarah Capello, Assistant Professor, Radford University on 1/18/22

The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text. read more

The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text.

The content is mostly accurate. I would have preferred a few nuances to be hashed out a bit further to avoid potential reader confusion or misunderstanding of the concepts presented.

The content is current; however, some of the references cited in the text are outdated. Newer editions of those texts exist.

The text is very accessible and readable for a variety of audiences. Key terms are well-defined.

There are no content discrepancies within the text. The author even uses similarly shaped graphics for recurring purposes throughout the text (e.g., arrow call outs for further reading, rectangle call outs for examples).

The content is chunked nicely by topics and sections. If it were used for a course, it would be easy to assign different sections of the text for homework, etc. without confusing the reader if the instructor chose to present the content in a different order.

The author follows the structure of the research process. The organization of the text is easy to follow and comprehend.

All of the supplementary images (e.g., tables and figures) were beneficial to the reader and enhanced the text.

There are no significant grammatical errors.

I did not find any culturally offensive or insensitive references in the text.

This text does the difficult job of introducing the complicated concepts and processes of quantitative research in a quick and easy reference guide fairly well. I would not depend solely on this text to teach students about quantitative research, but it could be a good jumping off point for those who have no prior knowledge on this subject or those who need a gentle introduction before diving in to more advanced and complex readings of quantitative research methods.

Reviewed by J. Marlie Henry, Adjunct Faculty, University of Saint Francis on 12/9/21

Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of... read more

Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of thought. There is no glossary but, for a guide of this length, a glossary does not seem like it would enhance the guide significantly.

The content is relatively accurate. Expanding the content a bit more or explaining that the methods and designs presented are not entirely inclusive would help. As there are different schools of thought regarding what should/should not be included in terms of these designs and methods, simply bringing attention to that and explaining a bit more would help.

Relevance/Longevity rating: 3

This content needs to be updated. Most of the sources cited are seven or more years old. Even more, it would be helpful to see more currently relevant examples. Some of the source authors such as Andy Field provide very interesting and dynamic instruction in general, but they have much more current information available.

The language used is clear and appropriate. Unnecessary jargon is not used. The intent is clear- to communicate simply in a straightforward manner.

The guide seems to be internally consistent in terms of terminology and framework. There do not seem to be issues in this area. Terminology is internally consistent.

For a guide of this length, the author structured this logically into sections. This guide could be adopted in whole or by section with limited modifications. Courses with fewer than seven modules could also logically group some of the sections.

This guide does present with logical organization. The topics presented are conceptually sequenced in a manner that helps learners build logically on prior conceptualization. This also provides a simple conceptual framework for instructors to guide learners through the process.

Interface rating: 4

The visuals themselves are simple, but they are clear and understandable without distracting the learner. The purpose is clear- that of learning rather than visuals for the sake of visuals. Likewise, navigation is clear and without issues beyond a broken link (the last source noted in the references).

This guide seems to be free of grammatical errors.

It would be interesting to see more cultural integration in a guide of this nature, but the guide is not culturally insensitive or offensive in any way. The language used seems to be consistent with APA's guidelines for unbiased language.

Reviewed by Heng Yu-Ku, Professor, University of Northern Colorado on 5/13/21

The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive... read more

The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive research study as an Appendix after section 7 (page 26) to help readers comprehend information better.

For the most part, the content is accurate and unbiased. However, the author only includes four types of research designs used on the social sciences that contain quantitative elements: 1. Mixed method, 2) Case study, 3) Quasi-experiment, and 3) Action research. I wonder why the correlational research is not included as another type of quantitative research design as it has been introduced and emphasized in section 6 by the author.

I believe the content is up-to-date and that necessary updates will be relatively easy and straightforward to implement.

The text is easy to read and provides adequate context for any technical terminology used. However, the author could provide more detailed information about estimating the minimum sample size but not just refer the readers to use the online sample calculators at a different website.

The text is internally consistent in terms of terminology and framework. The author provides the right amount of information with additional information or resources for the readers.

The text includes seven sections. Therefore, it is easier for the instructor to allocate or divide the content into different weeks of instruction within the course.

Yes, the topics in the text are presented in a logical and clear fashion. The author provides clear and precise terminologies, summarizes important content in Table or Figure forms, and offers examples in each section for readers to check their understanding.

The interface of the book is consistent and clear, and all the images and charts provided in the book are appropriate. However, I did encounter some navigation problems as a couple of links are not working or requires permission to access those (pages 10 and 27).

No grammatical errors were found.

No culturally incentive or offensive in its language and the examples provided were found.

As the book title stated, this book provides “A Quick Guide to Quantitative Research in Social Science. It offers easy-to-read information and introduces the readers to the research process, such as research questions, research paradigms, research process, research designs, research methods, data collection, data analysis, and data discussion. However, some links are not working or need permissions to access them (pages 10 and 27).

Reviewed by Hsiao-Chin Kuo, Assistant Professor, Northeastern Illinois University on 4/26/21, updated 4/28/21

As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and... read more

As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and process, discusses methods, data collection and analysis, and ends with writing a research report. It also identifies its target readers/users as those begins to explore quantitative research. It would be helpful to include more examples for readers/users who are new to quantitative research.

Its content is mostly accurate and no bias given its nature as a quick guide. Yet, it is also quite simplified, such as its explanations of mixed methods, case study, quasi-experimental research, and action research. It provides resources for extended reading, yet more recent works will be helpful.

The book is relevant given its nature as a quick guide. It would be helpful to provide more recent works in its resources for extended reading, such as the section for Survey Research (p. 12). It would also be helpful to include more information to introduce common tools and software for statistical analysis.

The book is written with clear and understandable language. Important terms and concepts are presented with plain explanations and examples. Figures and tables are also presented to support its clarity. For example, Table 4 (p. 20) gives an easy-to-follow overview of different statistical tests.

The framework is very consistent with key points, further explanations, examples, and resources for extended reading. The sample studies are presented following the layout of the content, such as research questions, design and methods, and analysis. These examples help reinforce readers' understanding of these common research elements.

The book is divided into seven chapters. Each chapter clearly discusses an aspect of quantitative research. It can be easily divided into modules for a class or for a theme in a research method class. Chapters are short and provides additional resources for extended reading.

The topics in the chapters are presented in a logical and clear structure. It is easy to follow to a degree. Though, it would be also helpful to include the chapter number and title in the header next to its page number.

The text is easy to navigate. Most of the figures and tables are displayed clearly. Yet, there are several sections with empty space that is a bit confusing in the beginning. Again, it can be helpful to include the chapter number/title next to its page number.

Grammatical Errors rating: 4

No major grammatical errors were found.

There are no cultural insensitivities noted.

Given the nature and purpose of this book, as a quick guide, it provides readers a quick reference for important concepts and terms related to quantitative research. Because this book is quite short (27 pages), it can be used as an overview/preview about quantitative research. Teacher's facilitation/input and extended readings will be needed for a deeper learning and discussion about aspects of quantitative research.

Reviewed by Yang Cheng, Assistant Professor, North Carolina State University on 1/6/21

It covers the most important topics such as research progress, resources, measurement, and analysis of the data. read more

It covers the most important topics such as research progress, resources, measurement, and analysis of the data.

The book accurately describes the types of research methods such as mixed-method, quasi-experiment, and case study. It talks about the research proposal and key differences between statistical analyses as well.

The book pinpointed the significance of running a quantitative research method and its relevance to the field of social science.

The book clearly tells us the differences between types of quantitative methods and the steps of running quantitative research for students.

The book is consistent in terms of terminologies such as research methods or types of statistical analysis.

It addresses the headlines and subheadlines very well and each subheading should be necessary for readers.

The book was organized very well to illustrate the topic of quantitative methods in the field of social science.

The pictures within the book could be further developed to describe the key concepts vividly.

The textbook contains no grammatical errors.

It is not culturally offensive in any way.

Overall, this is a simple and quick guide for this important topic. It should be valuable for undergraduate students who would like to learn more about research methods.

Reviewed by Pierre Lu, Associate Professor, University of Texas Rio Grande Valley on 11/20/20

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas. read more

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas.

Mostly accurate content.

As a quick guide, content is highly relevant.

Succinct and clear.

Internally, the text is consistent in terms of terminology used.

The text is easily and readily divisible into smaller sections that can be used as assignments.

I like that there are examples throughout the book.

Easy to read. No interface/ navigation problems.

No grammatical errors detected.

I am not aware of the culturally insensitive description. After all, this is a methodology book.

I think the book has potential to be adopted as a foundation for quantitative research courses, or as a review in the first weeks in advanced quantitative course.

Reviewed by Sarah Fischer, Assistant Professor, Marymount University on 7/31/20

It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable). read more

It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable).

Content Accuracy rating: 1

Contains VERY significant errors, such as saying that one can "accept" a hypothesis. (One of the key aspect of hypothesis testing is that one either rejects or fails to reject a hypothesis, but NEVER accepts a hypothesis.)

Very relevant to those experiencing the research process for the first time. However, it is written by someone working in the natural sciences but is a text for social sciences. This does not explain the errors, but does explain why sometimes the author assumes things about the readers ("hail from more subjectivist territory") that are likely not true.

Clarity rating: 3

Some statistical terminology not explained clearly (or accurately), although the author has made attempts to do both.

Very consistently laid out.

Chapters are very short yet also point readers to outside texts for additional information. Easy to follow.

Generally logically organized.

Easy to navigate, images clear. The additional sources included need to linked to.

Minor grammatical and usage errors throughout the text.

Makes efforts to be inclusive.

The idea of this book is strong--short guides like this are needed. However, this book would likely be strengthened by a revision to reduce inaccuracies and improve the definitions and technical explanations of statistical concepts. Since the book is specifically aimed at the social sciences, it would also improve the text to have more examples that are based in the social sciences (rather than the health sciences or the arts).

Reviewed by Michelle Page, Assistant Professor, Worcester State University on 5/30/20

This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new... read more

This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new researcher would not be able to use this as a stand alone guide for quantitative pursuits without having a supplemental text that explains the steps in the process more comprehensively. The introduction does provide this caveat.

Content Accuracy rating: 3

There are no biases or errors that could be distinguished; however, it’s simplicity in content, although accurate for an outline of process, may lack a conveyance of the deeper meanings behind the specific processes explained about qualitative research.

The content is outlined in traditional format to highlight quantitative considerations for formatting research foundational pieces. The resources/references used to point the reader to literature sources can be easily updated with future editions.

The jargon in the text is simple to follow and provides adequate context for its purpose. It is simplified for its intention as a guide which is appropriate.

Each section of the text follows a consistent flow. Explanation of the research content or concept is defined and then a connection to literature is provided to expand the readers understanding of the section’s content. Terminology is consistent with the qualitative process.

As an “outline” and guide, this text can be used to quickly identify the critical parts of the quantitative process. Although each section does not provide deeper content for meaningful use as a stand alone text, it’s utility would be excellent as a reference for a course and can be used as an content guide for specific research courses.

The text’s outline and content are aligned and are in a logical flow in terms of the research considerations for quantitative research.

The only issue that the format was not able to provide was linkable articles. These would have to be cut and pasted into a browser. Functional clickable links in a text are very successful at leading the reader to the supplemental material.

No grammatical errors were noted.

This is a very good outline “guide” to help a new or student researcher to demystify the quantitative process. A successful outline of any process helps to guide work in a logical and systematic way. I think this simple guide is a great adjunct to more substantial research context.

Table of Contents

• Section 1: What will this resource do for you?
• Section 2: Why are you thinking about numbers? A discussion of the research question and paradigms.
• Section 3: An overview of the Research Process and Research Designs
• Section 4: Quantitative Research Methods
• Section 5: the data obtained from quantitative research
• Section 6: Analysis of data
• Section 7: Discussing your Results

Ancillary Material

About the book.

This resource is intended as an easy-to-use guide for anyone who needs some quick and simple advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you area qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for maths, then this booklet should be a real help.

The booklet was amended in 2022 to take into account previous review comments.  

About the Contributors

Christine Davies , Ph.D

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Article Contents

• Introduction
• Quantitative research in social work
• Limitations
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Nature and Extent of Quantitative Research in Social Work Journals: A Systematic Review from 2016 to 2020

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• Supplementary Data

Sebastian Kurten, Nausikaä Brimmel, Kathrin Klein, Katharina Hutter, Nature and Extent of Quantitative Research in Social Work Journals: A Systematic Review from 2016 to 2020, The British Journal of Social Work , Volume 52, Issue 4, June 2022, Pages 2008–2023, https://doi.org/10.1093/bjsw/bcab171

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This study reviews 1,406 research articles published between 2016 and 2020 in the European Journal of Social Work (EJSW), the British Journal of Social Work (BJSW) and Research on Social Work Practice (RSWP). It assesses the proportion and complexity of quantitative research designs amongst published articles and investigates differences between the journals. Furthermore, the review investigates the complexity of the statistical methods employed and identifies the most frequently addressed topics. From the 1,406 articles, 504 (35.8 percent) used a qualitative methodology, 389 (27.7 percent) used a quantitative methodology, 85 (6 percent) used the mixed methods (6 percent), 253 (18 percent) articles were theoretical in nature, 148 (10.5 percent) conducted reviews and 27 (1.9 percent) gave project overviews. The proportion of quantitative research articles was higher in RSWP (55.4 percent) than in the EJSW (14.1 percent) and the BJSW (20.5 percent). The topic analysis could identify at least forty different topics addressed by the articles. Although the proportion of quantitative research is rather small in social work research, the review could not find evidence that it is of low sophistication. Finally, this study concludes that future research would benefit from making explicit why a certain methodology was chosen.

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The link between social work research and practice

When thinking about social work, some may consider the field to solely focus on clinical interventions with individuals or groups.

There may be a mistaken impression that research is not a part of the social work profession. This is completely false. Rather, the two have been and will continue to need to be intertwined.

This guide covers why social workers should care about research, how both social work practice and social work research influence and guide each other, how to build research skills both as a student and as a professional working in the field, and the benefits of being a social worker with strong research skills. 

A selection of social work research jobs are also discussed.  

• Social workers and research
• Evidence-based practice
• Practice and research
• Research and practice
• Build research skills
• Social worker as researcher
• Benefits of research skills
• Research jobs

Why should social workers care about research?

Sometimes it may seem as though social work practice and social work research are two separate tracks running parallel to each other – they both seek to improve the lives of clients, families and communities, but they don’t interact. This is not the way it is supposed to work.

Research and practice should be intertwined, with each affecting the other and improving processes on both ends, so that it leads to better outcomes for the population we’re serving.

Section 5 of the NASW Social Work Code of Ethics is focused on social workers’ ethical responsibilities to the social work profession. There are two areas in which research is mentioned in upholding our ethical obligations: for the integrity of the profession (section 5.01) and for evaluation and research (section 5.02). 

Some of the specific guidance provided around research and social work include:

• 5.01(b): …Social workers should protect, enhance, and improve the integrity of the profession through appropriate study and research, active discussion, and responsible criticism of the profession.
• 5.01(d): Social workers should contribute to the knowledge base of social work and share with colleagues their knowledge related to practice, research, and ethics…
• 5.02(a) Social workers should monitor and evaluate policies, the implementation of programs, and practice interventions.
• 5.02(b) Social workers should promote and facilitate evaluation and research to contribute to the development of knowledge.
• 5.02(c) Social workers should critically examine and keep current with emerging knowledge relevant to social work and fully use evaluation and research evidence in their professional practice.
• 5.02(q) Social workers should educate themselves, their students, and their colleagues about responsible research practices.

Evidence-based practice and evidence-based treatment

In order to strengthen the profession and determine that the interventions we are providing are, in fact, effective, we must conduct research. When research and practice are intertwined, this leads practitioners to develop evidence-based practice (EBP) and evidence-based treatment (EBT).

Evidence-based practice is, according to The National Association of Social Workers (NASW) , a process involving creating an answerable question based on a client or organizational need, locating the best available evidence to answer the question, evaluating the quality of the evidence as well as its applicability, applying the evidence, and evaluating the effectiveness and efficiency of the solution. 

Evidence-based treatment is any practice that has been established as effective through scientific research according to a set of explicit criteria (Drake et al., 2001). These are interventions that, when applied consistently, routinely produce improved client outcomes. 

For example, Cognitive Behavioral Therapy (CBT) was one of a variety of interventions for those with anxiety disorders. Researchers wondered if CBT was better than other intervention options in producing positive, consistent results for clients.

So research was conducted comparing multiple types of interventions, and the evidence (research results) demonstrated that CBT was the best intervention.

The anecdotal evidence from practice combined with research evidence determined that CBT should become the standard treatment for those diagnosed with anxiety. Now more social workers are getting trained in CBT methods in order to offer this as a treatment option to their clients.

How does social work practice affect research?

Social work practice provides the context and content for research. For example, agency staff was concerned about the lack of nutritional food in their service area, and heard from clients that it was too hard to get to a grocery store with a variety of foods, because they didn’t have transportation, or public transit took too long. 

So the agency applied for and received a grant to start a farmer’s market in their community, an urban area that was considered a food desert. This program accepted their state’s version of food stamps as a payment option for the items sold at the farmer’s market.

The agency used their passenger van to provide free transportation to and from the farmer’s market for those living more than four blocks from the market location.

The local university also had a booth each week at the market with nursing and medical students checking blood pressure and providing referrals to community agencies that could assist with medical needs. The agency was excited to improve the health of its clients by offering this program.

But how does the granting foundation know if this was a good use of their money? This is where research and evaluation comes in. Research could gather data to answer a number of questions. Here is but a small sample:

• How many community members visited each week and purchased fruits and vegetables? 
• How many took advantage of the transportation provided, and how many walked to the market? 
• How many took advantage of the blood pressure checks? Were improvements seen in those numbers for those having repeat blood pressure readings throughout the market season? 
• How much did the self-reported fruit and vegetable intake increase for customers? 
• What barriers did community members report in visiting and buying food from the market (prices too high? Inconvenient hours?)
• Do community members want the program to continue next year?
• Was the program cost-effective, or did it waste money by paying for a driver and for gasoline to offer free transportation that wasn’t utilized? What are areas where money could be saved without compromising the quality of the program?
• What else needs to be included in this program to help improve the health of community members?

How does research affect social work practice?

Research can guide practice to implement proven strategies. It can also ask the ‘what if’ or ‘how about’ questions that can open doors for new, innovative interventions to be developed (and then research the effectiveness of those interventions).

Engel and Schutt (2017) describe four categories of research used in social work:

• Descriptive research is research in which social phenomena are defined and described. A descriptive research question would be ‘How many homeless women with substance use disorder live in the metro area?’
• Exploratory research seeks to find out how people get along in the setting under question, what meanings they give to their actions, and what issues concern them. An example research question would be ‘What are the barriers to homeless women with substance use disorder receiving treatment services?’
• Explanatory research seeks to identify causes and effects of social phenomena. It can be used to rule out other explanations for findings and show how two events are related to each other.  An explanatory research question would be ‘Why do women with substance use disorder become homeless?’
• Evaluation research describes or identifies the impact of social programs and policies. This type of research question could be ‘How effective was XYZ treatment-first program that combined housing and required drug/alcohol abstinence in keeping women with substance use disorder in stable housing 2 years after the program ended?’

Each of the above types of research can answer important questions about the population, setting or intervention being provided. This can help practitioners determine which option is most effective or cost-efficient or that clients are most likely to adhere to. In turn, this data allows social workers to make informed choices on what to keep in their practice, and what needs changing. 

How to build research skills while in school

There are a number of ways to build research skills while a student.  BSW and MSW programs require a research course, but there are other ways to develop these skills beyond a single class:

• Volunteer to help a professor working in an area of interest. Professors are often excited to share their knowledge and receive extra assistance from students with similar interests.
• Participate in student research projects where you’re the subject. These are most often found in psychology departments. You can learn a lot about the informed consent process and how data is collected by volunteering as a research participant.  Many of these studies also pay a small amount, so it’s an easy way to earn a bit of extra money while you’re on campus. 
• Create an independent study research project as an elective and work with a professor who is an expert in an area you’re interested in.  You’d design a research study, collect the data, analyze it, and write a report or possibly even an article you can submit to an academic journal.
• Some practicum programs will have you complete a small evaluation project or assist with a larger research project as part of your field education hours. 
• In MSW programs, some professors hire students to conduct interviews or enter data on their funded research projects. This could be a good part time job while in school.
• Research assistant positions are more common in MSW programs, and these pay for some or all your tuition in exchange for working a set number of hours per week on a funded research project.

How to build research skills while working as a social worker

Social service agencies are often understaffed, with more projects to complete than there are people to complete them.

Taking the initiative to volunteer to survey clients about what they want and need, conduct an evaluation on a program, or seeing if there is data that has been previously collected but not analyzed and review that data and write up a report can help you stand out from your peers, be appreciated by management and other staff, and may even lead to a raise, a promotion, or even new job opportunities because of the skills you’ve developed.

Benefits of being a social worker with strong research skills

Social workers with strong research skills can have the opportunity to work on various projects, and at higher levels of responsibility. 

Many can be promoted into administration level positions after demonstrating they understand how to conduct, interpret and report research findings and apply those findings to improving the agency and their programs.

There’s also a level of confidence knowing you’re implementing proven strategies with your clients. 

Social work research jobs

There are a number of ways in which you can blend interests in social work and research. A quick search on Glassdoor.com and Indeed.com retrieved the following positions related to social work research:

• Research Coordinator on a clinical trial offering psychosocial supportive interventions and non-addictive pain treatments to minimize opioid use for pain.
• Senior Research Associate leading and overseeing research on a suite of projects offered in housing, mental health and corrections.
• Research Fellow in a school of social work
• Project Policy Analyst for large health organization
• Health Educator/Research Specialist to implement and evaluate cancer prevention and screening programs for a health department
• Research Interventionist providing Cognitive Behavioral Therapy for insomnia patients participating in a clinical trial
• Research Associate for Child Care and Early Education
• Social Services Data Researcher for an organization serving adults with disabilities.
• Director of Community Health Equity Research Programs evaluating health disparities.

No matter your population or area of interest, you’d likely be able to find a position that integrated research and social work. 

Social work practice and research are and should remain intertwined. This is the only way we can know what questions to ask about the programs and services we are providing, and ensure our interventions are effective. 

There are many opportunities to develop research skills while in school and while working in the field, and these skills can lead to some interesting positions that can make a real difference to clients, families and communities. 

Drake, R. E., Goldman, H., Leff, H. S., Lehman, A. F., Dixon, L., Mueser, K. T., et al. (2001). Implementing evidence-based practices in routine mental health service settings. Psychiatric Services, 52(2), 179-182. 

Engel, R.J., & Schutt, R.K. (2017). The Practice of Research in Social Work. Sage.

National Association of Social Workers. (n.d). Evidence Based Practice. Retrieved from: https://www.socialworkers.org/News/Research-Data/Social-Work-Policy-Research/Evidence-Based-Practice

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Focusing on what matters - research and evidence in social work

Published: 15 November 2018

Since I took up the post of the Chief Social Worker for Adults in England, one of my enduring priorities has been to encourage the development and use of research and evidence to inform social work practice and improve life outcomes for the people we serve.

Understanding which approaches and interventions work best and gathering the evidence to support them is essential. Why must we do this? To sustain and improve social work as part of the wider social care and health offer. This is how we will continue to deliver high quality care and support, centred on people's strengths, needs and aspirations.

For social workers and other social care professionals, having access to quality research and evidence is increasingly important. It supports decision making and challenges ingrained thinking and ways of working that are often taken for granted.

I am really pleased that the NIHR is helping raise the profile, and investing in social care and social work research.

The social care sector must be recognised and valued for the difference it makes to people’s lives and be put on an equal footing with health. Only then can we ensure the whole system really does achieve integrated outcomes for people, making the best use of all available approaches and resources.

The sector itself is recognising this imperative. The Professional Capabilities Framework (PCF) which underpins all social workers’ professional development has been updated to include greater reference to the importance of research and evidence-informed practice.

However, for people in contact with social care services, decisions made about which areas to research can often seem remote and disconnected from the reality of their lives and the things that matter to them.

That is why I am so pleased to welcome the publication of the  James Lind Alliance (JLA)  report setting out the priorities for adult social work research.

Developed using their tried and tested methods, this is the first time anywhere in the world that this kind of research prioritisation has happened for adult social work and the first time the JLA approach has been used in a non-health related area.

Their approach is unique in fully involving people who use services, their carers and practitioners in identifying the questions that social work research should answer. Over 1150 people were involved in narrowing the field to  a final top 10 , which covers a diverse range of issues and themes for adult social work.

This report is a critical first step in helping us to make sure that future research answers the questions that are important, both to social workers and to those who are - or have been - in contact with them. I would ask all of you to read and share this report and to consider developing the research capability in your organisations and partnerships. More than that, I want you to encourage people and their carers, social workers and academics, to come together to shape and use research to make a real difference to people’s lives.

I look forward to working with you as we start the process of turning these questions into research. This is our opportunity to transform the quality of social work practice and social care support for the many individuals and families we strive to help.

• This blog was originally published on  Lyn Romeo's blog on gov.uk .
• The NIHR is running a campaign to raise awareness of social care and social work research. Find out more on the  NIHR website .

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