importance of research to a social worker

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So why is research important to social work?

As social workers, we train to be able to see the multitude of invisible lines within the systems that hold our lives together, or divide us. We learn to recognize the disconnects, and to help our clients figure out how to reconnect the dots. We view the world through a lens of person-in-environment, that is to say, we seek to understand the context in which our clients live.

The social sciences have an inherent obligation not only to keep abreast of current relevant research, but also to be competent enough to apply new treatments and insights within their practice. Social workers are truly dedicated professionals who have to complete a minimum number of continuing education credits to continue practicing. We don’t get to pick and choose the individuals we help, which is why we have to constantly develop our cultural competencies to identify the strengths of those we are helping. So, research is important to social work because it helps us be effective!

According to the NASW, research in social work helps us:

• Assess the needs and resources of people in their environments
• Evaluate the effectiveness of social work services in meeting peoples needs
• Demonstrate relative costs and benefits of social work services
• Advance professional education in light of changing contexts for practice
• Understand the impact of legislation and social policy on the clients and communities we serve (Retrieved from http://www.socialworkpolicy.org/research)

I still do not know what my research question will be for my senior thesis, but I am beginning to pare down some topics that interest me such as:

• Effects of childhood trauma
• The school-to-prison pipeline
• Trauma-informed therapies within prisons
• Effectiveness of prison diversion programs

8 thoughts on “ So why is research important to social work? ”

try explaining in detail

article quite informing for an amateur in research

In doing any of interventions;evidence based is needed. Not intuition,you need to do assessment of the problem before intervention.Then again you need to to evaluation on the service you provided if has positive impact to your client.

It is a very informative piece of work

try explaining in detail the points listed as to where the nexus between Research and Social work lie

are there means to conduct dual research projects with your institutions?

Akulu muziika zithu zonse ap tisamachiteso kuvutika iyayi 😏😏

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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

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.

Learn more about how you can earn your  Master of Social Work online at Virginia Commonwealth University . The highest-ranking school of social work in Virginia, VCU has a wide range of courses online. That means students can earn their degrees with the flexibility of learning at home. Learn more about how you can take your career in social work further with VCU.

From M.S.W. to LCSW: Understanding Your Career Path as a Social Worker

How Palliative Care Social Workers Support Patients With Terminal Illnesses

How to Become a Social Worker in Health Care

Gov.uk, Mixed Methods Study

MVS Open Press, Foundations of Social Work Research

Open Social Work Education, Scientific Inquiry in Social Work

Open Social Work, Graduate Research Methods in Social Work: A Project-Based Approach

Routledge, Research for Social Workers: An Introduction to Methods

SAGE Publications, Research Methods for Social Work: A Problem-Based Approach

Theory and Society, Mixed Methods Research: What It Is and What It Could Be

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1 1. Science and social work

Chapter outline.

• How do social workers know what to do? (12 minute read time)
• The scientific method (16 minute read time)
• Evidence-based practice (11 minute read time)
• Social work research (10 minute read time)

Content warning: Examples in this chapter contain references to school discipline, child abuse, food insecurity, homelessness, poverty and anti-poverty stigma, anti-vaccination pseudoscience, autism, trauma and PTSD, mental health stigma, susto and culture-bound syndromes, gender-based discrimination at work, homelessness, psychiatric hospitalizations, substance use, and mandatory treatment.

1.1 How do social workers know what to do?

Learning objectives.

Learners will be able to…

• Reflect on how we, as social workers, make decisions
• Differentiate between micro-, meso-, and macro-level analysis
• Describe the concept of intuition, its purpose in social work, and its limitations
• Identify specific errors in thinking and reasoning

What would you do?

Case 1: Imagine you are a clinical social worker at a children’s mental health agency. One day, you receive a referral from your town’s middle school about a client who often skips school, gets into fights, and is disruptive in class. The school has suspended him and met with the parents on multiple occasions, who say they practice strict discipline at home. Yet the client’s behavior has worsened. When you arrive at the school to meet with your client, who is also a gifted artist, you notice he seems to have bruises on his legs, has difficulty maintaining eye contact, and appears distracted. Despite this, he spends the hour painting and drawing, during which time you are able to observe him.

• Given your observations of your client’s strengths and challenges, what intervention would you select, and how could you determine its effectiveness?

Case 2: Imagine you are a social worker working in the midst of an urban food desert (a geographic area in which there is no grocery store that sells fresh food). As a result, many of your low-income clients either eat takeout, or rely on food from the dollar store or a convenience store. You are becoming concerned about your clients’ health, as many of them are obese and say they are unable to buy fresh food. Your clients tell you that they have to rely on food pantries because convenience stores are expensive and often don’t have the right kinds of food for their families. You have spent the past month building a coalition of community members to lobby your city council. The coalition includes individuals from non-profit agencies, religious groups, and healthcare workers.

• How should this group address the impact of food deserts in your community?  What intervention(s) do you suggest?  How would you determine whether your intervention was effective?

Case 3: You are a social worker working at a public policy center whose work focuses on the issue of homelessness. Your city is seeking a large federal grant to address this growing problem and has hired you as a consultant to work on the grant proposal. After interviewing individuals who are homeless and conducting a needs assessment in collaboration with local social service agencies, you meet with city council members to talk about potential opportunities for intervention. Local agencies want to spend the money to increase the capacity of existing shelters in the community. In addition, they want to create a transitional housing program at an unused apartment complex where people can reside upon leaving the shelter, and where they can gain independent living skills. On the other hand, homeless individuals you interview indicate that they would prefer to receive housing vouchers to rent an apartment in the community. They also fear the agencies running the shelter and transitional housing program would impose restrictions and unnecessary rules and regulations, thereby curbing their ability to freely live their lives. When you ask the agencies about these client concerns, they state that these clients need the structure and supervision provided by agency support workers.

• Which kind of program should your city choose to implement?  Which is most likely to be effective and why?

Assuming you’ve taken a social work course before, you will notice that these case studies cover different levels of analysis in the social ecosystem—micro, meso, and macro. At the micro-level , social workers examine the smallest levels of interaction; in some cases, just “the self” alone (e.g. the child in case one).

When social workers investigate groups and communities, such as our food desert in case 2, their inquiry is at the meso-level .

At the  macro-level , social workers examine social structures and institutions. Research at the macro-level examines large-scale patterns, including culture and government policy.

These three domains interact with one another, and it is common for a research project to address more than one level of analysis. For example, you may have a study about individuals at a case management agency (a micro-level study) that impacts the organization as a whole (meso-level) and incorporates policies and cultural issues (macro-level). Moreover, research that occurs on one level is likely to have multiple implications across domains.

How do social workers know what to do?

Welcome to social work research. This chapter begins with three problems that social workers might face in practice, and three questions about what a social worker should do next. If you haven’t already, spend a minute or two thinking about the three aforementioned cases and jot down some notes. How might you respond to each of these cases?

I assume it is unlikely you are an expert in the areas of children’s mental health, community responses to food deserts, and homelessness policy. Don’t worry, I’m not either. In fact, for many of you, this textbook will likely come at an early point in your graduate social work education, so it may seem unfair for me to ask you what the ‘right’ answers are. And to disappoint you further, this course will not teach you the ‘right’ answer to these questions. It will, however, teach you how to answer these questions for yourself, and to find the ‘right’ answer that works best in each unique situation.

Assuming you are not an experienced practitioner in the areas described above, you likely used intuition (Cheung, 2016). [1] when thinking about what you would do in each of these scenarios. Intuition is a “gut feeling” about what to think about and do, often based on personal experience. What we experience influences how we perceive the world. For example, if you’ve witnessed representations of trauma in your practice, personal life, or in movies or television, you may have perceived that the child in case one was being physically abused and that his behavior was a sign of trauma. As you think about problems such as those described above, you find that certain details stay with you and influence your thinking to a greater degree than others. Using past experiences, you apply seemingly relevant knowledge and make predictions about what might be true.

Over a social worker’s career, intuition evolves into practice   wisdom . Practice wisdom is the “learning by doing” that develops as a result of practice experience. For example, a clinical social worker may have a “feel” for why certain clients would be a good fit to join a particular therapy group. This idea may be informed by direct experience with similar situations, reflections on previous experiences, and any consultation they receive from colleagues and/or supervisors. This “feel” that social workers get for their practice is a useful and valid source of knowledge and decision-makin – do not discount it.

On the other hand, intuitive thinking can be prone to a number of errors. We are all limited in terms of what we know and experience. One’s economic, social, and cultural background will shape intuition, and acting on your intuition may not work in a different sociocultural context. Because you cannot learn everything there is to know before you start your career as a social worker, it is important to learn how to understand and use social science to help you make sense of the world and to help you make sound, reasoned, and well-thought out decisions.

Social workers must learn how to take their intuition and deepen or challenge it by engaging with scientific literature. Similarly, social work researchers engage in research to make certain their interventions are effective and efficient (see Section 1.4 for more information). Both of these processes–consuming and producing research–inform the social justice mission of social work. That’s why the Council on Social Work Education (CSWE), who accredits the MSW program you are in, requires that you engage in social science.

Competency 4: Engage In Practice-informed Research and Research-informed Practice Social workers understand quantitative and qualitative research methods and their respective roles in advancing a science of social work and in evaluating their practice. Social workers know the principles of logic, scientific inquiry, and culturally informed and ethical approaches to building knowledge. Social workers understand that evidence that informs practice derives from multi-disciplinary sources and multiple ways of knowing. They also understand the processes for translating research findings into effective practice. Social workers: • use practice experience and theory to inform scientific inquiry and research; • apply critical thinking to engage in analysis of quantitative and qualitative research methods and research findings; and • use and translate research evidence to inform and improve practice, policy, and service delivery. (CSWE, 2015). [2]

Errors in thinking

We all rely on mental shortcuts to help us figure out what to do in a practice situation. All people, including you and me, must train our minds to be aware of predictable flaws in thinking, termed cognitive biases . Here is a link to the Wikipedia entry on cognitive biases, as well as an interactive list . As you can see, there are many types of biases that can results in irrational conclusions.

The most important error in thinking for social scientists to be aware of is the concept of confirmation bias . Confirmation bias involves observing and analyzing information in a way that confirms what you already believe to be true. We all arrive at each moment with a set of personal beliefs, experiences, and worldviews that have been developed and ingrained over time. These patterns of thought inform our intuitions, primarily in an unconscious manner. Confirmation bias occurs when our mind ignores or manipulates information to avoid challenging what we already believe to be true.

In our second case study, we are trying to figure out how to help people who receive SNAP (sometimes referred to as Food Stamps) who live in a food desert. Let’s say we have arrived at a policy solution and are now lobbying the city council to implement it. There are many who have negative beliefs about people who are “on welfare.”  These people may believe individuals who receive social welfare benefits spend their money irresponsibly, are too lazy to get a job, and manipulate the system to maintain or increase their government payout.

Those espousing this belief may point to an example such as Louis Cuff , who bought steak and lobster with his SNAP benefits and resold them for a profit. However, they are falling prey to assuming that one person’s bad behavior reflects upon an entire group of people. City council members who hold these beliefs may ignore the truth about the client population—that people experiencing poverty usually spend their money responsibly and that they genuinely need help accessing fresh and healthy food. In this way, confirmation bias often makes people less capable of empathizing with one another because they have difficulty accepting alternative perspectives.

Errors in reasoning

Because the human mind is prone to errors, when anyone makes a statement about what is true or what should be done in a given situation, errors in logic may abound. Think back to the case studies at the beginning of this section. You most likely had some ideas about what to do in each case. Below are some of the most common logical fallacies and the ways in which they may negatively influence a social worker:

• Making hasty generalization : when a person draws conclusions before having enough information. A social worker may apply lessons from a handful of clients to an entire population of people (see Louis Cuff , above). It is important to examine the scientific literature in order to avoid this.
• Confusing correlation with causation : when one concludes that because two things are correlated (as one changes, the other changes), they must be causally related. As an example, a social worker might observe both an increase in the minimum wage and higher unemployment in certain areas of the city. However, just because two things changed at the same time does not mean they are causally related. Social workers should explore other factors that might impact causality.
• Going down a slippery slope : when a person concludes that we should not do something because something far worse will happen if we do so. For example, a social worker may seek to increase a client’s opportunity to choose their own activities, but face opposition from those who believe it will lead to clients making unreasonable demands. Clearly, this is nonsense. Changes that foster self-determination are unlikely to result in client revolt. Social workers should be skeptical of arguments opposing small changes because one argues that radical changes are inevitable.
• Appealing to authority : when a person draws a conclusion by appealing to the authority of an expert or reputable individual, rather than through the strength of the claim. You have likely encountered individuals who believe they are correct because another in a position of authority told them so. Instead, we should work to build a reflective and critical approach to practice that questions authority.
• Hopping on the bandwagon : when a person draws a conclusion consistent with popular belief. Just because something is popular does not mean it is correct. Fashionable ideas come and go. Social workers should engage with trendy ideas but must ground their work in scientific evidence rather than popular opinion.
• Using a straw man : when a person does not represent their opponent’s position fairly or with sufficient depth. For example, a social worker advocating for a new group home may depict homeowners that are opposed to clients living in their neighborhood as individuals concerned only with their property values. However, this may not be the case. Social workers should instead engage deeply with all sides of an issue and represent them accurately.

Key Takeaways

• Social work research occurs at the micro-, meso-, and macro-level.
• Intuition is a powerful, though limited, source of information when making decisions.
• All human thought is subject to errors in thinking and reasoning.
• Scientific inquiry accounts for cognitive biases by applying an organized, logical way of observing and theorizing about the world.
• Think about a social work topic you might want to study this semester as part of a research project. How do individuals commit specific errors in logic or reasoning when discussing a specific topic (e.g. Louis Cuff)? How can using scientific evidence help you combat popular myths that are based on erroneous thinking?
• Reflect on the strengths and limitations of your personal experiences as a way to guide your work with diverse populations. Describe an instance when your intuition may have resulted in biased or misguided thinking or behavior in a social work practice situation.

1.2 The scientific method

Learning objectives.

• Define science and social science
• Describe the differences between objective and subjective truth(s)
• Identify how qualitative and quantitative data are analyzed differently and how they can be used together
• Delineate the features of science that distinguish it from pseudoscience

If I asked you to draw a picture of science, what would you draw?  My guess is it would be something from a chemistry or biology classroom, like a microscope or a beaker. Maybe something from a science fiction movie. All social workers use scientific thinking in their practice. However, social workers have a unique understanding of what science means, one that is (not surprisingly) more open to the unexpected and human side of the social world.

Science and not-science

In social work, science is a way of ‘knowing’ that attempts to systematically collect and categorize facts or truths. A key word here is systematically –conducting science is a deliberate process. Scientists gather information about facts in a way that is organized and intentional, and usually follows a set of predetermined steps. Social work is not a science, but social work is informed by social science ; the science of humanity, social interactions, and social structures. In other words, social work research uses organized and intentional procedures to uncover facts or truths about the social world. And social workers rely on social scientific research to promote change.

Science can also be thought of in terms of its impostor, pseudoscience. Pseudoscience refers to beliefs about the social world that are unsupported by scientific evidence. These claims are often presented as though they are based on science. But once researchers test them scientifically, they are demonstrated to be false. A scientifically uninformed social work practitioner using pseudoscience may recommend any number of ineffective, misguided, or harmful interventions. Pseudoscience often relies on information and scholarship that has not been reviewed by experts or offers a selective and biased reading of reviewed literature.

An example of pseudoscience comes from anti-vaccination activists. Despite overwhelming scientific consensus that vaccines do not cause autism, a very vocal minority of people continue to believe that they do. Anti-vaccination advocates present their information as based in science, as seen here at Green Med Info . The author of this website shares real abstracts from scientific journal articles and studies but will only provide information on articles that show the potential dangers of vaccines, without showing any research that prevents the positive and safe side of vaccines. Green Med Info is an example of confirmation bias, as all data presented on the website supports what the pseudo-scientific researcher believes to be true. For more information on assessing causal relationships, consult Chapter 6 , where we discuss causality in detail.

The values and practices associated with the scientific method work to overcome common errors in thinking (such as confirmation bias). First, the scientific method uses established techniques from the literature to determine the likelihood of something being true or false. The research process often cites these techniques, reasons for their use, and how researchers came to the decision to use said techniques. However, each technique comes with its own strengths and limitations. Rigorous science is about making the best choice, being open about your process, and allowing others to check your work. It is important to remember that there is no “perfect” study – all research has limitations because all scientific methods come with limitations.

Skepticism and debate

Unfortunately, the “perfect” researcher does not exist. Scientists are human, so they are subject to error and bias, such as gravitating toward fashionable ideas and thinking their work is more important than others’ work. Theories and concepts fade in and out of use and may be tossed aside when new evidence challenges their truth. Part of the challenge in your research projects will be finding what you believe about an issue, rather than summarizing what others think about the topic. Good science, just like good social work practice, is authentic. When I see students present their research projects, those that are the strongest deliver both passionate and informed arguments about their topic area.

Good science is also open to ongoing questioning. Scientists are fundamentally skeptical. As such, they are likely to pursue alternative explanations. They might question the design of a study or replicate it to see if it works in another context. Scientists debate what is true until they arrive at a majority consensus. If you’ve ever heard that 97% of climate scientists agree that global warming is due to human activity [3] or that 99% of economists agree that tariffs make the economy worse [4] , you are seeing this sociology of science in action. This skepticism will help to catch situations in which scientists who make the oh-so-human mistakes in thinking and reasoning reviewed in Section 1.1.

Skepticism also helps to identify unethical scientists, as with Andrew Wakefield’s study linking the MMR vaccination and autism. When other researchers looked at his data, they found that he had altered the data to match his own conclusions and sought to benefit financially from the ensuing panic about vaccination (Godlee, Smith, & Marcovitch, 2011). [5] This highlights another key value in science: openness.

Through the use of publications and presentations, scientists share the methods used to gather and analyze data. The trend towards open science has also prompted researchers to share data as well. This in turn enables other researchers to re-run, replicate, and validate analyses and results. A major barrier to openness in science is the paywall. When you’ve searched online for a journal article (we will review search techniques in Chapter 3), you have likely run into the $25-$50 price tag. Don’t despair – your university should subscribe to these journals. However, the push towards openness in science means that more researchers are sharing their work in open access journals, which are free for people to access (like this textbook!). These open access journals do not require a university subscription to view.

Openness also means engaging the broader public about your study. Social work researchers conduct studies to help people, and part of scientific work is making sure your study has an impact. For example, it is likely that many of the authors publishing in scientific journals are on Twitter or other social media platforms, relaying the importance of study findings. They may create content for popular media, including newspapers, websites, blogs, or podcasts. It may lead to training for agency workers or public administrators. Regrettably, academic researchers have a reputation for being aloof and disengaged from the public conversation. However, this reputation is slowly changing with the trend towards public scholarship and engagement. For example, see this recent section of the Journal of the Society of Social Work and Research on public impact scholarship .

Science supported by empirical data

Pseudoscience is often doctored up to look like science, but the surety with which its advocates speak is not backed up by empirical data. Empirical data refers to information about the social world gathered and analyzed through scientific observation or experimentation. Theory is also an important part of science, as we will discuss in Chapter 5 . However, theories must be supported by empirical data–evidence that what we think is true really exists in the world.

There are two types of empirical data that social workers should become familiar with. Quantitative data refers to numbers and  qualitative data usually refers to word data (like a transcript of an interview) but can also refer to pictures, performances, and other means of expressing oneself. Researchers use specific methods designed to analyze each type of data. Together, these are known as research methods , or the methods researchers use to examine empirical data.

Objective truth

In our vaccine example, scientists have conducted many studies tracking children who were vaccinated to look for future diagnoses of autism (see Taylor et al. 2014 for a review). This is an example of using quantitative data to determine whether there is a causal relationship between vaccination and autism. By examining the number of people who develop autism after vaccinations and controlling for all of the other possible causes, researchers can determine the likelihood of whether vaccinations cause changes in the brain that are eventually diagnosed as autism.

In this case, the use of quantitative data is a good fit for disproving myths about the dangers of vaccination. When researchers analyze quantitative data, they are trying to establish an objective truth. An objective truth is always true, regardless of context. Generally speaking, researchers seeking to establish objective truth tend to use quantitative data because they believe numbers don’t lie. If repeated statistical analyses don’t show a relationship between two variables, like vaccines and autism, that relationship almost certainly does not exist. By boiling everything down to numbers, we can minimize the biases and logical errors that human researchers bring to the scientific process. That said, the interpretation of those numbers is always up for debate. That process can be subjective.

This approach to finding truth probably sounds similar to something you heard in your middle school science classes. When you learned about gravitational force or the mitochondria of a cell, you were learning about the theories and observations that make up our understanding of the physical world. We assume that gravity is real and that the mitochondria of a cell are real. Mitochondria are easy to spot with a powerful microscope and we can observe and theorize about their function in a cell. The gravitational force is invisible, but clearly apparent from observable facts, such as watching an apple fall. If we were unable to perceive mitochondria or gravity, they would still be there, doing their thing, because they exist independent of our observation of them.

Let’s consider a social work example. Scientific research has established that children who are subjected to severely traumatic experiences are more likely to be diagnosed with a mental health disorder (e.g., Mahoney, Karatzias, & Hutton, 2019). [6] A diagnosis of post-traumatic stress disorder (PTSD) is considered objective, and may refer to a mental health issue that exists independent of the individual observing it and is highly similar in its presentation across clients. The Diagnostic and Statistical Manual of Mental Disorders (DSM-5, 2017) [7] identifies a group of criteria which is based on unbiased, neutral client observations. These criteria are based in research, and render an objective diagnosis more likely to be valid and reliable. Through the clinician’s observations and the client’s description of their symptoms, an objective determination of a mental health diagnosis can be made.

Subjective truth(s)

For those of you skeptics, you may ask yourself: but does a diagnosis tell a client’s whole story? No. It does not tell you what the client thinks and feels about their diagnosis, for example. Receiving a diagnosis of PTSD may be a relief for a client. The diagnosis may suggest the words to describe their experiences. In addition, this diagnosis may provide a direction for therapeutic work, as there are evidence-based interventions clinicians can use with each diagnosis. On the other hand, a client may feel shame and view the diagnosis as a label, defining them in a negative way and limiting their potential (Barsky, 2015). [8]

Imagine if we surveyed people with PTSD to see how they interpreted their diagnosis. Objectively, we could determine whether more people said the diagnosis was, overall, a positive or negative event for them. However, it is unlikely that the experience of receiving a diagnosis was either completely positive or completely negative. In social work, we know that a client’s thoughts and emotions are rarely binary, either/or situations. Clients likely feel a mix of positive and negative thoughts and emotions during the diagnostic process. These messy bits are subjective truths , or the thoughts and feelings that arise as people interpret and make meaning of situations. Uniquely, looking for subjective truths can help us see the contradictory and multi-faceted nature of people’s thoughts, and qualitative data allows us to avoid oversimplifying them into negative and positive feelings that could be counted, as in quantitative data. It is the role of a researcher, just like a practitioner, to seek to understand things from the perspective of the client. Unlike with objective truth, this will not lead to a general sense of what is true for everyone, but rather what is true for that one person.

Subjective truths are best expressed through qualitative data, or through the use of words (not numbers). For example, we might invite a client to tell us how they felt after they were first diagnosed, after they spoke with family, and over the course of the therapeutic process. While it may look different from what we normally think of as science (e.g. pharmaceutical studies), these stories are indeed a rich source of data for scientific analysis. However, it is impossible to analyze what this client said without also considering the sociocultural context in which they live. For example, the concept of PTSD is generated from Western thought and philosophy. How might people from other cultures understand trauma differently?

In the DSM-5 classification of mental health disorders, there is a list of culture-bound syndromes which appear only in certain cultures. For example,  susto describes a unique cluster of symptoms experienced by Latin Americans after a traumatic event (Nogueira, Mari, & Razzouk, 2015). [9]   Susto involves more physical symptoms than a traditional PTSD diagnosis. Indeed, many of these syndromes do not fit within a Western conceptualization of mental health because they differentiate less between the mind and body. To a Western scientist, susto may seem less real than PTSD. To someone from Latin America, their symptoms may not fit neatly into the PTSD framework developed in Western nations . Science has historically privileged knowledge from the United States and other nations in the West and Global North , marking them as objectively true. The objectivity of Western science as universally applicable to all cultures has been increasingly called into question as science has become less dominated by white males, and interaction between cultures and groups becomes broadly more democratic. Clearly, what is true depends in part on the context in which it is observed.

In this way, social scientists have a unique task. People are both objects and subjects. Objectively, you could quantify how tall a person is, what car they drive, how many adverse childhood experiences they had, or their score on a PTSD checklist. Subjectively, you could understand how a person made sense of a traumatic incident or how it contributed to certain patterns in thinking, negative feelings, or opportunities for growth, for example. It is this added dimension that renders social science unique to natural science, which focuses almost exclusively on quantitative data and objective truth. For this reason, this book is divided between projects using qualitative data and quantitative data.

There is no “better” or “more true” way of approaching social science. Instead, the methods a researcher chooses should match the question they ask. If you want to answer, “do vaccines cause autism?” you should choose methods appropriate to answer that question. It seeks an objective truth–one that is true for everyone, regardless of context. Studies like these use quantitative data and statistical analyses to test mathematical relationships between variables. If, on the other hand, you wanted to know “what does a diagnosis of PTSD mean to clients?” you should collect qualitative data and seek subjective truths. You will gather stories and experiences from clients and interpret them in a way that best represents their unique and shared truths. Where there is consensus, you will report that. Where there is contradiction, you will report that as well.

Mixed methods

In this textbook, we will treat quantitative and qualitative research methods separately. However, it is important to remember that a project can include both approaches. A mixed methods study, which we will discuss more in chapter 6, requires thinking through a more complicated project that includes at least one quantitative component, one qualitative component, and a plan to incorporate both approaches together. As a result, mixed methods projects may require more time for conceptualization, data collection, and analysis.

Finding patterns

Regardless of whether you are seeking objective or subjective truths, research and scientific inquiry aim to find and explain patterns. Most of the time, a pattern will not explain every single person’s experience, a fact about social science that is both fascinating and frustrating. Even individuals who do not know each other can create patterns that persist over time. Those new to social science may find these patterns frustrating because they may believe that the patterns describing their sex, age, or some other facet of their lives don’t represent their experience. It’s true. A pattern can exist among your cohort without your individual participation in it. There is diversity within diversity.

Let’s consider some specific examples. You probably wouldn’t be surprised to learn that a person’s social class background has an impact on their educational attainment and achievement. You may be surprised to learn that people select romantic partners that have similar educational attainment, which in turn, impacts their children’s educational attainment (Eika, Mogstad, & Zafar, 2019). [10] . People who have graduated college pair off with other college graduates, as so forth. This, in turn, reinforces existing inequalities, stratifying society by those who have the opportunity to complete college and those who don’t.

People who object to these findings tend to cite evidence from their own personal experience. However, the problem with this response is that objecting to a social pattern on the grounds that it doesn’t match one’s individual experience misses the point about patterns. Patterns don’t perfectly predict what will happen to an individual person. Yet, they are a reasonable guide that, when systematically observed, can help guide social work thought and action. When we don’t investigate these patterns scientifically, we are subject to developing stereotypes, biases, and other harmful beliefs.

A final note on qualitative and quantitative methods

There is not one superior way to find patterns that help us understand the world. As we will learn about in Chapter 5 , there are multiple philosophical, theoretical, and methodological ways to approach scientific truth. Qualitative methods aim to provide an in-depth understanding of a relatively small number of cases. They also provide a voice for the client. Quantitative methods offer less depth on each case but can say more about broad patterns because they typically focus on a much larger number of cases. A researcher should approach the process of scientific inquiry by formulating a clear research question and using the methodological tools best suited to that question.

Believe it or not, there are still significant methodological battles being waged in the academic literature on objective vs. subjective social science. Usually, quantitative methods are viewed as “more scientific” and qualitative methods are viewed as “less scientific.”  Part of this battle is historical. As the social sciences developed, they were compared with the natural sciences, especially physics, which rely on mathematics and statistics to come to a truth. It is a hotly debated topic whether social science should adopt the philosophical assumptions of the natural sciences—with its emphasis on prediction, mathematics, and objectivity—or use a different set of tools—contextual understanding, language, and subjectivity—to find scientific truth.

You are fortunate to be in a profession that values multiple scientific ways of knowing. The qualitative/quantitative debate is fueled by researchers who may prefer one approach over another, either because their own research questions are better suited to one particular approach or because they happened to have been trained in one specific method. In this textbook, we’ll operate from the perspective that qualitative and quantitative methods are complementary rather than competing. While these two methodological approaches certainly differ, the main point is that they simply have different goals, strengths, and weaknesses. A social work researcher should select the method(s) that best match(es) the question they are asking.

• Social work is informed by science.
• Social science is concerned with both objective and subjective knowledge.
• Social science research aims to understand patterns in the social world.
• Social scientists use both qualitative and quantitative methods, which, while different, are often complementary.

Examine a pseudoscientific claim you’ve heard on the news or in conversation with others. Why do you consider it to be pseudoscientific? What empirical data can you find from a quick internet search that would demonstrate it lacks truth?

• Consider a topic you might want to study this semester as part of a research project. Provide a few examples of objective and subjective truths about the topic, even if you aren’t completely certain they are correct. Identify how objective and subjective truths differ.

1.3 Evidence-based practice

• Explain how social workers produce and consume research as part of practice
• Review the process of evidence-based practice and how social workers apply research knowledge with clients and groups

“Why am I in this class?”

“When will I ever use this information?”

While students aren’t always so direct, I would wager a guess that these questions are on the mind of almost every student in a research methods class. And they are valid and important questions to ask!  While it may seem strange, the answer is that you will probably use these skills often. Social workers engage with research on a daily basis by consuming it through popular media, social work education, and advanced training. They also often contribute to research projects, adding new scientific information to what we know. As professors, we also sometimes hear from field supervisors who say that research competencies are unimportant in their setting. One might wonder how these organizations measure program outcomes, report the impact of their program to board members or funding agencies, or create new interventions grounded in social theory and empirical evidence.

Social workers as research consumers

Whether you know it or not, your life is impacted by research every day. Many of our laws, social policies, and court proceedings are grounded in some degree of empirical research and evidence (Jenkins & Kroll-Smith, 1996). [11] That’s not to say that all laws and social policies are good or make sense. But you can’t have an informed opinion about any of them without understanding where they come from, how they were formed, and what their evidence base is. In order to be effective practitioners across micro, meso, and macro domains, social workers need to understand the root causes and policy solutions to social problems their clients are experiencing.

A recent lawsuit against Walmart provides an example of social science research in action. A sociologist named Professor William Bielby was enlisted by plaintiffs to conduct an analysis of Walmart’s personnel policies in order to support their claim that Walmart engages in gender discriminatory practices. Bielby’s analysis shows that Walmart’s compensation and promotion decisions may indeed have been vulnerable to gender bias. In June 2011, the United States Supreme Court decided against allowing the case to proceed as a class-action lawsuit ( Wal-Mart Stores, Inc. v. Dukes , 2011). [12] While a class-action suit was not pursued in this case, consider the impact that such a suit against one of our nation’s largest employers could have had on companies, their employees, and even consumers around the country. [13]

A social worker might learn about this lawsuit through popular media, news media websites or television programs. Social science knowledge allows a social worker to apply a critical eye towards new information, regardless of the source. Unfortunately, popular media does not always report on scientific findings accurately. A social worker armed with scientific knowledge would be able to search for, read, and interpret the original study as well as other information that might challenge or support the study. As social work graduate students, you should be comfortable in your information literacy abilities, and your advocacy and practice should be grounded in these skills. Chapters 2, 3, and 4 of this textbook focus on information literacy , or how to understand what we already know about a topic and contribute to that body of knowledge.

When social workers consume research, they are usually doing so to inform their practice. Clinical social workers are required by a state licensing board to complete continuing education classes in order to remain informed on the latest information in their field. On the macro side, social workers at public policy think tanks consume information to inform advocacy and public awareness campaigns. Regardless of the role of the social worker, practice must be informed by research.

Evidence-based practice

Consuming research is the first component of evidence-based practice (EBP). Drisko and Grady (2015) [14] present EBP as a process composed of “four equally weighted parts: 1) current client needs and situation, (2) the best relevant research evidence, (3) client values and preferences, and (4) the clinician’s expertise” (p. 275). It is not simply “doing what the literature says,” but is rather a process by which practitioners examine the literature, client, self, and context to inform interventions with clients and systems (McNeese & Thyer, 2004). [15] It is a collaboration between social worker, client, and context. As we discussed in Section 1.2, the patterns discovered by scientific research are not applicable to all situations. Instead, we rely on our critical thinking skills to apply scientific knowledge to real-world situations.

The bedrock of EBP is a proper assessment of the client or client system. Once we have a solid understanding of what the issue is, we can evaluate the literature to determine whether there are any interventions that have been shown to treat the issue, and if so, which have been shown to be the most effective. You will learn those skills in the next few chapters. Once we know what our options are, we should be upfront with clients about each option, what the interventions look like, and what the expected outcome will be. Once we have client feedback, we use our expertise and practice wisdom to make an informed decision about how to move forward.

If this sounds familiar, it’s the same approach a doctor, physical therapist, or other health professional would use. This highlights a common critique of EBP: it is too focused on micro-level, clinical social work practice. Not every social worker is a clinical social worker. While there is a large body of literature on EBP for clinical practice, the same concepts apply to other social work roles as well. A social work manager should endeavor to be familiar with evidence-based management styles, and a social work policy advocate should argue for evidence-based policies.

In agency-based social work practice, EBP can take on a different role due to the complexities of the grant funding process. Funders naturally require agencies to demonstrate that their practice is effective. Agencies are almost always required to document that they are achieving the outcomes they intended. However, funders sometimes require agencies to choose from a limited list of interventions determined to be evidence-based practices. Not included in this model are clinical expertise and client values, which are key components of EBP and the therapeutic process. According to some funders, EBP is not a process conducted by a practitioner but instead consists of a list of interventions. Similar dynamics are at play in private clinical practice, in which insurance companies may specify the modality of therapy offered. For example, insurance companies may favor short-term, solution-focused therapy which minimizes cost. But what happens when someone has an idea for a new kind of intervention?  How do new approaches get “on the list” of EBPs of grant funders?

Social workers as research producers

Innovation in social work is incredibly important. Social workers work on wicked problems for their careers. For those of you who have practice experience, you may have had an idea of how to better approach a practice situation. That is another reason you are here in a research methods class. You (really!) will have bright ideas about what to do in practice. Sam Tsemberis relates an “ Aha! ” moment from his practice in this Ted talk on homelessness . While a faculty member at the New York University School of Medicine, he noticed a problem with people cycling in and out of the local psychiatric hospital wards. Clients would arrive in psychiatric crisis, stabilize under medical supervision in the hospital, and end up back at the hospital in psychiatric crisis shortly after discharge.

When he asked the clients what their issues were, they said they were unable to participate in homelessness programs because they were not always compliant with medication for their mental health diagnosis and they continued to use drugs and alcohol. The housing supports offered by the city government required abstinence and medication compliance before one was deemed “ready” for housing. For these clients, the problem was a homelessness service system that was unable to meet clients where they were–ready for housing, but not ready for abstinence and psychiatric medication. As a result, chronically homeless clients were cycling in and out of psychiatric crises, moving back and forth from the hospital to the street.

The solution that Sam Tsemberis implemented and popularized is called Housing First , and is an approach to homelessness prevention that starts by, you guessed it, providing people with housing first and foremost. Tsemberis’s model addresses chronic homelessness in people with co-occurring disorders (those who have a diagnosis of a substance use and mental health disorder). The Housing First model states that housing is a human right: clients should not be denied their right to housing based on substance use or mental health diagnoses.

In Housing First programs, clients are provided housing as soon as possible. The Housing First agency provides wraparound treatment from an interdisciplinary team, including social workers, nurses, psychiatrists, and former clients who are in recovery. Over the past few decades, this program has gone from a single program in New York City to the program of choice for federal, state, and local governments seeking to address homelessness in their communities.

The main idea behind Housing First is that once clients have a residence of their own, they are better able to engage in mental health and substance use treatment. While this approach may seem logical to you, it is the opposite of the traditional homelessness treatment model. The traditional approach began with the client abstaining from drug and alcohol use and taking prescribed medication. Only after clients achieved these goals were they offered group housing. If the client remained sober and medication compliant, they could then graduate towards less restrictive individual housing.

Conducting and disseminating research allows practitioners to establish an evidence base for their innovation or intervention, and to argue that it is more effective than the alternatives, and should therefore be implemented more broadly. For example, by comparing clients who were served through Housing First with those receiving traditional services, Tsemberis could establish that Housing First was more effective at keeping people housed and at addressing mental health and substance use goals. Starting first with smaller studies and graduating to larger ones, Housing First built a reputation as an effective approach to addressing homelessness. When President Bush created the Collaborative Initiative to Help End Chronic Homelessness in 2003, Housing First was used in a majority of the interventions and its effectiveness was demonstrated on a national scale. In 2007, it was acknowledged as an evidence-based practice in the Substance Abuse and Mental Health Services Administration’s (SAMHSA) EBP resource center. [16]

We suggest browsing around the SAMHSA EBP Resource Center and looking for interventions on topics that interest you. Other sources of evidence-based practices include the Cochrane Reviews digital library  and Campbell Collaboration . In the next few chapters, we will talk more about how to search for and locate literature about clinical interventions. The use of systematic reviews , meta-analyses , and randomized controlled trials are particularly important in this regard, types of research we will describe more in Chapter 3 and Chapter 4.

So why share the story of Housing First? Well, we want you to think about what you hope to contribute to our knowledge of social work practice. What is your bright idea and how can it change the world? Practitioners innovate all the time, often incorporating those innovations into their agency’s approach and mission. Using scientific research methods, agency-based social workers can demonstrate to policymakers and other social workers that their innovations should be more widely used. Without this wellspring of new ideas, social services would not be able to adapt to the changing needs of their communities. Social workers in agency-based practice may also participate in research projects taking place at their agency. Partnerships between schools of social work and agencies are a common way of testing and implementing innovations in social work. In such a case, all parties receive an advantage: clinicians receive specialized training, clients receive additional services, agencies gain prestige, and researchers can illustrate the effectiveness of an intervention.

Evidence-based practice highlights the unique perspective that social work brings to research. Social work both “holds” and critiques evidence. With regard to the former, “holding” evidence refers to the fact that the field of social work values scientific information. The Housing First example demonstrates how this interplay between valuing and critiquing science works–first by critiquing existing research and conducting research to establish a new approach to a problem. It also demonstrates the importance of listening to your target population and privileging their understanding and perception of the issue. While their understanding is not the result of scientific inquiry, it is deeply informed through years of direct experience with the issue and embedded within the relevant cultural and historical context. Although science often searches for the “one true answer,” social work researchers must remain humble about the degree to which we can really know, and must begin to engage with other ways of knowing that may originate from clients and communities.

See the video  below for an example of how “one true answer” about a population can often oversimplify things and overstate how much we know about how to intervene in a given situation.

Cultural Humility: People, Principles and Practices – Part 1 of 4 by Vivian Chavez is adapted under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) http://creativecommons.org/licenses/b…

While you may not become a scientist in the sense of wearing a lab coat and using a microscope, social workers must understand science in order to engage in ethical practice. In this section, we reviewed ways in which research is a part of social work practice, including:

• Determining the best intervention for a client or system
• Ensuring existing services are accomplishing their goals
• Satisfying requirements to receive funding from private agencies and government grants
• Testing a new idea and demonstrating that it should be more widely implemented

Using a social work practice situation that you have experienced, walk through the four steps of the evidence-based practice process and how they informed your decision-making. Reflect on some of the difficulties applying EBP in the real world.

• Talk with a social worker about how he or she produces and consumes research as part of practice. Consider asking them about articles that changed their practice or helped them think about a problem in a new way. They may talk more about a training or a book, rather than academic journal articles. Reflect on your personal career goals and how research will fit into your future practice.

1.4 Social work research

• Differentiate between formal and informal research roles
• Describe common barriers to engaging with social work research
• Identify alternative ways of thinking about research methods

Formal and informal research roles

I’ve been teaching research methods for six years and have found that many students struggle to see the connection between research and social work practice. First of all, it’s important to mention that social work researchers exist!  The authors of this textbook are social work researchers across university, government, and non-profit institutions. Matt and Cory are researchers at universities, focusing on disability policy, wellness & mental health, and intimate partner violence. Dalia is a behavioral health researcher at RTI International, a nonprofit research institute, where she studies the opioid epidemic. Kate is a researcher at the Joint Legislative Audit and Review Commission in Virginia, where she studies policies related to criminal justice. The career path for social workers in formal research roles is bright and diverse, as we each bring a unique perspective with our ethical and theoretical orientation.

Formal research results in written products like journal articles, government reports, or policy briefs. To get a sense of formal research roles in social work, consider asking a professor about their research. You can also browse around the top journals in social work: Trauma, Violence & Abuse , Child Maltreatment , Child Abuse & Neglect , Social Service Review , Family Relations , Journal of Social Policy , Social Policy & Administration , Research on Social Work Practice , Health & Social Care in the Community , Health & Social Work , British Journal of Social Work , Child & Family Social Work , International Journal of Social Welfare , Qualitative Social Work , Children & Youth Services Review , Social Work , Social Work in Health Care , Journal of Social Work Practice , International Social Work , Affilia Journal of Women and Social Work , and Clinical Social Work Journal .  Additionally, the websites to most government agencies, foundations, think tanks, and advocacy groups contain formal research often conducted by social workers.

But let’s be clear, studies show that most social work students are not interested in becoming social work researchers who publish journal articles or research reports (DeCarlo et al., 2019; Earley, 2014). [17] Once you enter post-graduate practice, you will need to apply your formal research skills to the informal research conducted by practitioners and agencies every day. Every time you are asking who, what, when, where and why, you are conducting informal research. Informal research can be more involved. Social workers may be surprised when they are asked to engage in research projects such as needs assessments, community scans, program and policy evaluations, and single system designs, to name a few. Macro-oriented students may have to conduct research on programs and policies as part of advocacy or administration. I cannot tell you the number former students who have contacted me looking for research resources or wanting to “pick my brain” about research they are doing as part of their employment.

Research for action

Regardless of whether a social worker conducts formal research that results in journal articles or informal research that is used within an agency, all social work research is distinctive in that it is active (Engel & Schutt, 2016). [18] We want our results to be used to effect social change. Sometimes this means using findings to change how clients receive services. Sometimes it means using findings to show the benefits of programs or policies. Sometimes it means using findings to speak with those oppressed and marginalized persons who have been left out of the policy creation process. Additionally, it can mean using research as the mode with which to engage a constituency to address a social justice issue. All of these research activities differ; however, the one consistent ingredient is that these activities move us towards social and economic justice.

Student anxieties and beliefs about research

Unfortunately, students generally arrive in research methods classes with a mixture of dread, fear, and frustration. If you attend any given social work education conference, there is probably a presentation on how to better engage students in research. There is an entire body of academic research that verifies what any research professor knows to be true. Honestly, this is why the authors of this textbook started this project. We want to make research more enjoyable and engaging for students. Generally, we have found some common myths and misconceptions get in the way of student success in research. Let’s see if any of these match with what you are thinking.

I’m never going to use this crap!

Students who tell me that research methods is not useful to them are saying something important. As a student scholar, your most valuable asset is your time. You give your time to the subjects you consider important to you and for your career. Because most social workers don’t become researchers or practitioner-researchers, students may feel that a research methods class is a waste of time. Our discussion of evidence-based practice and the ways in which social workers use research in practice brought home the idea that social workers play an important role in creating and disseminating new knowledge about social services.

On a more immediate level, learning about research methods and completing an individual research project allow students to focus in on a specific topic. This class is an invitation to conduct an independent study on a social work topic of interest to you. In this book, you will learn how to understand and apply the scientific method to that topic. Not only that, but the skills you learn in literature search and review will help you in every class in your MSW program.

Research is only for super-smart people

Research methods involves a lot of terminology that may be entirely new to social work students. Other domains of social work, such as practice, are easier to apply your intuition towards. You understand how to be an empathetic person, and your experiences in life can help guide you through a practice situation or even a theoretical or conceptual question. Research may seem like a totally new area in which you have no previous experience. In research methods there can be “wrong” answers. Depending on your research question, some approaches to data analysis or measurement, for example, may not help you find the correct answer.

The fear is entirely understandable. Research is not straightforward. As Figure 1.1 shows, it is a process that is non-linear, involving multiple revisions, wrong turns, and dead ends before you figure out the best question and research approach. You may have to go back to chapters after having read them or even peek ahead at chapters your class hasn’t covered yet.

Moreover, research is something you learn by doing…and stumbling a few times. It’s an iterative process, or one that requires many tries to get right. There isn’t a shortcut for learning research, but if you follow along with the exercises in this book, you can break down a student research project and accomplish it piece by piece. No one just knows research. It’s something you pick up by doing it, reflecting on the experiences and results, redoing your work, and revising it in consultation with your professor and peers. Research involves exploration, risk taking, and a willingness to say, “Let’s see what we will find!”

Research is designed to suck the joy from my life

We’ve talked already about the arcane research terminology, so I won’t go into it again here. But students sometimes perceive research methods as boring. Practice knowledge and even theory are fun to learn because they are easy to apply and provide insights into the world around you. Research just seems like its own weirdly shaped and ill-fitting puzzle piece.

I completely understand where this perspective comes from and hope there are a few things you will take away from this course that aren’t boring to you. In the first section of this textbook, you will learn how to take any topic and learn what is known about it. It may seem trivial, but this is actually a superpower. Your social work education will teach you basic knowledge that can be applied to nearly all social work practice situations as well as some applied material applicable to specific social work practice situations. However, no education will provide you with everything you need to know. And certainly, no professor can tell you what will be discovered over the next few decades of your practice. Our work on literature reviews in the next few chapters will help you increase your skills and knowledge to become a strong social work student and practitioner. Following that, our exploration of research methods will help you understand how theories, practice models, and techniques you learn in other classes are created and tested scientifically. Like a colorful puzzle, you’ll see how all of the pieces fit together.

Get out of your own way

Together, these misconceptions and myths can create a self-fulfilling prophecy for students. If you believe research is boring, you won’t find it interesting. If you believe research is hard, you will struggle more with assignments. If you believe research is useless, you won’t see its utility. If you’re afraid that you will make mistakes, then you won’t want to try. While we certainly acknowledge that students aren’t going to love research as much as we do (we spent over a year writing this book, so we like it a lot!), we suggest reframing how you think about research using the following touchstones:

• All social workers rely on social science research to engage in competent practice.
• No one  already knows research. It’s something I’ll learn through practice. And it’s challenging for everyone, not just me.
• Research is relevant to me because it allows me to figure out what is known about any topic I want to study.
• If the topic I choose to study is important to me, I will be more interested in exploring research to help me understand it further.

Students should be intentional about managing any anxiety coming from a research project. Here are some suggestions:

• Talk to your professor if you are feeling lost. We like students!
• Talk to a librarian if you are having trouble finding information about your topic.
• Seek support from your peers or mentors.

The structure of this textbook

The textbook is divided into five parts. In the first part (Chapters 1-4), we will review how to orient your research proposal to a specific question you want to answer and review the literature to see what we know about it. Student research projects come with special limitations, as you don’t have many resources, so our chapters are designed to help you think through those limitations and think of a project that is doable. In the second part (Chapters 5-8), we will bring in theory, causality, ethics to help you conceptualize your research project and what you hope to achieve. By the end of the second part, you will create a quantitative and qualitative research question. Parts 3 and 4 will walk you through how to conduct quantitative and qualitative research, respectively. These parts run through how to recruit people to participate in your study, what to ask them, and how to interpret the results of what they say. Finally, the last part of the textbook reviews how to connect research and practice. For some, that will mean completing program evaluations as part of agency-based practice. For others, it will mean consuming research as part of continuing education as a practitioner. We hope you enjoy reading this book as much as we enjoyed writing it!

If you are still figuring out how to navigate the book using your internet browser, consider watching our tutorial [LINK NEEDED]. Also, the exercises in each chapter offer you an opportunity to apply what you wrote to your own research project, so consider completing these as you read.

• Social workers engage in formal and informal research production as part of practice.
• If you feel anxious, bored, or overwhelmed by research, you are not alone!
• Becoming more familiar with research methods will help you become a better scholar and social work practitioner.
• With your peers, explore your feelings towards your research methods classes. Describe some themes that come up during your conversations. Identify which issues can be addressed by your professor and which can be addressed by students.
• Browse social work journals and identify an article of interest to you. Look up the author’s biography or curriculum vitae on their personal website or the website of their university.
• Cheung, J. C. S. (2016). Researching practice wisdom in social work. Journal of Social Intervention: Theory and Practice ,  25 (3), 24-38. ↵
• For more on the CSWE accreditation standards see https://www.cswe.org/CSWE/media/AccredidationPDFs/2015-epas-and-glossary_1.pdf and the EPAS index in this book. ↵
• See: https://climate.nasa.gov/faq/17/do-scientists-agree-on-climate-change/ ↵
• See: http://www.igmchicago.org/surveys/import-duties ↵
• Godlee   F. ,  Smith   J. , & Marcovitch   H . (2011) Wakefield’s article linking MMR vaccine and autism was fraudulent. British medical journal, 342 , 64-66. ↵
• Mahoney, A., Karatzias, T., & Hutton, P. (2019). A systematic review and meta-analysis of group treatments for adults with symptoms associated with complex post-traumatic stress disorder.  Journal of affective disorders ,  243 , 305-321. ↵
• American Psychiatric Association. (2017). Diagnostic and statistical manual of mental disorders (5th ed.) . Washington, DC ↵
• Barsky, A. (2015). DSM-5 and the ethics of diagnosis. New social worker . Retrieved from: https://www.socialworker.com/feature-articles/ethics-articles/dsm-5-and-ethics-of-diagnosis/ ↵
• Nogueira, B. L., Mari, J. D. J., & Razzouk, D. (2015). Culture-bound syndromes in Spanish speaking Latin America: the case of Nervios, Susto and Ataques de Nervios. Archives of Clinical Psychiatry (São Paulo), 42( 6), 171-178. ↵
• Eika, L., Mogstad, M., & Zafar, B. (2019). Educational assortative mating and household income inequality. Journal of Political Economy, 127 (6), 2795-2835. ↵
• Jenkins, P. J., & Kroll-Smith, S. (Eds.). (1996). Witnessing for sociology: Sociologists in court . Westport, CT: Praeger. ↵
• Wal-Mart  Stores, Inc. v. Dukes , 564 U.S. (2011). The American Sociological Association (ASA) subsequently filed an amicus brief in support of what would be the class of individuals claiming gender discrimination. You can read the brief at http://asanet.org/images/press/docs/pdf/Amicus_Brief_Wal-Mart_v Dukes_et_al.pdf.  For other recent amicus briefs filed by the ASA, see  http://asanet.org/about/amicus_briefs.cfm . ↵
• Want to know more about the suit against Walmart or about Bielby’s analysis for the case? Check out the following source: Hart, M., & Secunda, P. M. (2009). A matter of context: Social framework evidence in employment discrimination class actions. Fordham Law Review ,  78 , 37-70. (2009). A matter of context: Social framework evidence in employment discrimination class action.  Fordham Law Review, 78 , 37–70. Retrieved from:  http://www.fordhamlawreview.org/assets/pdfs/Vol_78/Hart_Secunda_October_2009.pdf ↵
• Drisko, J. W., & Grady, M. D. (2015). Evidence-based practice in social work: A contemporary perspective. Clinical Social Work Journal ,  43 (3), 274-282. ↵
• McNeece, C. A., & Thyer, B. A. (2004). Evidence-based practice and social work. Journal of evidence-based social work ,  1 (1), 7-25. ↵
• Substance Abuse and Mental Health Services Administration (2007). Pathways' housing first program . Retrieved from:https://www.samhsa.gov/homelessness-programs-resources/hpr-resources/housing-first-supports-recovery ↵
• DeCarlo, M. P., Schoppelrey, S., Crenshaw, C., Secret, M. C., & Stewart, M. (2020, January 1). Open educational resources and graduate social work students: Cost, outcomes, use, and perceptions. https://doi.org/10.31235/osf.io/k4ytd; Earley, M. A. (2014). A synthesis of the literature on research methods education. Teaching in Higher Education, 19 (3), 242-253. ↵
• Engel, R. J. & Schutt, R. K. (2016) The practice of research in social work (4th edition) . Washington, DC: Sage Publications ↵

examining the smallest levels of interaction, usually individuals

examining interaction between groups and within communities

examining social structures and institutions

a “gut feeling” about what to do based on previous experience

“learning by doing” that guides social work intervention and increases over time

predictable flaws in thinking

observing and analyzing information in a way that agrees with what you already think is true and excludes other alternatives

a way of knowing that attempts to systematically collect and categorize facts or truths

the science of humanity, social interactions, and social structures

claims about the world that appear scientific but are incompatible with the values and practices of science

information about the social world gathered and analyzed through scientific observation or experimentation

numerical data

data derived from analysis of texts. Usually, this is word data (like a conversation or journal entry) but can also include performances, pictures, and other means of expressing ideas.

the methods researchers use to examine empirical data

a single truth, observed without bias, that is universally applicable

one truth among many, bound within a social and cultural context

a process composed of "four equally weighted parts: 1) current client needs and situation, (2) the best relevant research evidence, (3) client values and preferences, and (4) the clinician’s expertise" (Drisko & Grady, 2015, p. 275)

a study that combines raw data from multiple quantitative studies and analyzes the pooled data using statistics

Graduate research methods in social work Copyright © 2020 by Matthew DeCarlo, Cory Cummings, Kate Agnelli is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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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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NASW members can access articles online at: Social Work Research

Social Work Research publishes exemplary research to advance the development of knowledge and inform social work practice. Widely regarded as the outstanding journal in the field, it includes analytic reviews of research, theoretical articles pertaining to social work research, evaluation studies, and diverse research studies that contribute to knowledge about social work issues and problems.

Career Tips , Choosing a Job , Getting a Job

Navigating the Path to Social Work Careers

Published: May 24, 2024

Social work is a deeply rewarding field where you can make a significant impact on individual lives and communities. You might be drawn to social work because it provides a tangible way to help others, or perhaps you want to be on the front lines of social change. Let’s take a closer look at the profession below.

Social Work Careers

Social work is a field with a wide range of career opportunities, each offering the chance to make a significant difference in the lives of others. Whether through direct client interaction or community-wide programs, social workers play a crucial role in improving societal well-being.

The core values of social work are service, social justice, dignity, and integrity. These four values guide practitioners in their professional actions and their commitment to serving individuals and communities effectively. 

Social workers fill roles in a variety of sectors, including healthcare, education, community, nonprofit, and government. The best career in social work is different for each person and depends on that person’s strengths along with the type of work they are passionate about. Below are some of the most popular careers in social work.

Clinical Social Work Therapist

Clinical social work therapists specialize in diagnosing and treating mental, emotional, and behavioral disorders.

Medical Social Worker

Medical social workers work in healthcare settings to help patients navigate the emotional and practical challenges associated with acute, chronic, or terminal illnesses.

School Social Worker

School support workers support student success by addressing social, emotional, and behavioral problems that interfere with education.

Hospice Social Worker

Hospice social workers provide end-of-life support to patients and their families, helping them manage psychological and logistical challenges.

Substance Use and Recovery Treatment Counselor

Substance use and recovery treatment counselors assist individuals recovering from addiction, providing counseling and support to help them reclaim control of their lives.

Mental Health Counselor

Mental health counselors offer therapy and support for individuals dealing with mental health issues.

Community Service Manager

Community service managers oversee programs and staff that provide social services to the public.

Health Educator

Health educators focus on community-wide health education and intervention to promote wellness and healthy living.

Child and Family Social Worker

Child and family social workers work with children and families to improve situations in cases of abuse, neglect, or parental incapacity.

Social Research Scientist

Social research scientists research to evaluate and improve social services systems.

What Does a Social Worker Do?

Social workers fulfill a variety of critical functions in their daily roles. These tasks demonstrate the comprehensive nature of social work, requiring a blend of empathy, problem-solving skills , and practical knowledge of social services. Here’s a more detailed look at a social worker’s typical tasks.

Client Assessment

Social workers begin their intervention with a thorough assessment of the client’s needs, strengths, and challenges. This process includes interviewing clients, and possibly their families, to gather detailed social, economic, and psychological information.

Developing Plans 

Based on their assessments, social workers develop tailored intervention plans to address the client’s specific circumstances. This might involve setting goals, outlining steps to meet those goals, and identifying appropriate resources.

Resource Connection

A key task is to connect clients with community resources and services. This can include mental health services, healthcare, housing, job training, and more, depending on what the client needs to improve their situation.

Social workers often act as advocates for their clients to access services and resources. They may work to change policies or access resources that are not readily available, ensuring that clients receive necessary services, such as healthcare or legal aid.

Crisis Intervention

In urgent situations, such as cases of abuse or mental health crises, social workers intervene to provide immediate support and safety. They are trained to handle emergencies and can provide critical support services during crises.

Counseling and Support

Counseling is a fundamental part of social work. This includes therapeutic interventions aimed at helping individuals cope with their circumstances and improving their emotional and psychological well-being.

Monitoring and Evaluation

After implementing intervention plans, social workers monitor the progress of their clients and evaluate the effectiveness of the intervention. Adjustments to the plan may be made to better meet the client’s needs.

Documentation

Accurate documentation is crucial in social work. Social workers keep detailed records of assessments, plans, client progress, and sessions. This documentation ensures continuity of care and accountability.

What are the Benefits of Being a Social Worker?

The field of social work comes with a variety of benefits, including the ability to help others, a diverse working environment, and personal growth. One of the most fulfilling aspects of being a social worker is the opportunity to make a positive impact on individuals, families, and communities. Social workers play a crucial role in mental health care, crisis intervention, and employment counseling, often seeing firsthand how their efforts improve the lives of those they help. This aspect of the job provides a deep sense of purpose and accomplishment, which is a significant source of job satisfaction.

In addition to personal fulfillment, social work offers a diverse work environment where professionals can interact with people from various backgrounds and experiences. This diversity enriches the job experience, fostering a broader understanding and appreciation of different perspectives and needs. Social work also supports professional development through ongoing training and educational opportunities, allowing practitioners to stay current in their field and advance in their careers. 

How to Become a Social Worker?

The path to becoming a social worker typically begins with obtaining a bachelor’s degree in social work or a related field such as psychology, sociology, or health sciences. This foundational step provides the essential knowledge and skills needed in the profession, including an understanding of social welfare policy, human behavior, and ethical practice. 

UoPeople offers a comprehensive bachelor of science in health science program, with an opportunity to earn a certificate in behavioral health . This program offers a curriculum in human development, psychopathology and mental health, community health, biology, and bioethics. You will gain an in-depth understanding of how social, cultural, and biological factors contribute to mental health and will prepare you for the next career step.

Besides offering a top-notch education, UoPeople’s courses are taught completely online , making our programs a great fit for students who are working or juggling family responsibilities. Because of our flexible model, our courses contain a diverse mix of students from around the world, providing unique perspectives and networking opportunities unmatched by in-person programs.

Once you have completed a bachelor’s degree, aspiring social workers who wish to enter clinical practice or advance in their careers typically pursue a Master of Social Work (MSW) degree. An MSW not only broadens their knowledge and expertise but also meets the educational requirements for licensure, which is mandatory for clinical social workers in most states. 

After earning an MSW, candidates must complete a period of supervised clinical experience, often two to three years, before they can apply for licensure. The final steps include passing a professional state licensing exam and fulfilling any additional state-specific requirements.

Choosing a career in social work offers an exceptional opportunity to positively impact the lives of individuals, families, and entire communities. Social workers stand at the forefront of addressing societal challenges, from advocating for social justice to providing critical mental health support. 

This profession is not just a job; it’s a calling that attracts those who wish to make a meaningful difference. The role of a social worker extends beyond mere occupation—it’s about fostering change, supporting resilience, and empowering the most vulnerable to achieve their full potential. It’s a career that embodies the spirit of service, making it deeply fulfilling for those who pursue it.

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Mental health in the workplace: a conversation bridging research and practice

How can we promote mental health in the workplace .

This is a question that Zhiqing (Albert) Zhou , PhD, and Lawanda Lewis are constantly asking themselves in their work, just from different perspectives. As an associate professor in the Department of Mental Health, Dr. Zhou researches how employees’ work-related experiences impact their health, well-being, and safety. As an HR Business Partner who oversees multiple academic departments at the Bloomberg School, Ms. Lewis has firsthand experience with assessing the mental health needs of employees and the effectiveness of workplace mental health and wellness programs. 

This Mental Health Awareness Month, we brought them together for a wide-ranging conversation about research, practice, program implementation, and what still needs to be learned to help workplaces manage and support the mental health of their employees.

This conversation has been edited and condensed for length and clarity.

Lawanda Lewis: Post-COVID, we’re seeing different work modalities, from fully remote work to hybrid work to a mix. Hybrid work seems to be the way of the world now. What approaches can organizations take to better promote mental wellness in a hybrid workforce?

Albert Zhou:  There is consistent evidence of the benefits of hybrid work, such as more flexibility, more autonomy, reducing commuting time, and better work-life balance. Meanwhile, there are reports of remote or hybrid workers feeling lonely or isolated, dealing with the added stress of shared spaces and family responsibilities, and feeling pressure to always appear available and present. We published a study in 2022 in the International Journal of Human Resource Management that found that workers’ mental health was negatively impacted when they felt too closely monitored by their managers.

One way to deal with this is to make sure managers are trained to prepare, support, and better communicate expectations and guidelines for hybrid and remote workers, while giving workers flexibility and more control over their time. Social and emotional support from coworkers and supervisors is also instrumental to building a healthy work life. People should be able to ask questions, connect with their colleagues, and access resources regardless of when and where they’re working. My collaborators and I are trying to understand how hybrid or remote work can be better managed so that workers can enjoy the benefits and reduce the negative consequences for their mental health.

LL: What has recent research revealed about the mental health benefits of transitioning to a four-day work week with no pay reduction?

AZ: We still need to do more research on the four-day work week, and we don’t yet have consistent solutions, even though this topic has been discussed for over 50 years. But there have been pilots and case studies in several countries that have shown evidence of increased productivity. Workers in these studies reported that they are more satisfied with their work, have better work life balance, and experience less stress and burnout. However, one issue that came up is scheduling problems. For example, I’m working for four days, but my clients are not, so how can we align our work? When we studied weekly work cycles , we found that Monday is already the most stressful day. Since working on Friday is off the table, how do I make sure too much work doesn’t pile up on Monday? 

It’s important to note that these pilot programs were tested with a small number of organizations who voluntarily participated, which means they were already open to the idea of a four-day work week. It's unclear, then, whether their practices can be generalized to other workplaces. The transition to a four-day work week may be easier for office workers, but it would be harder for people in industries where people’s work schedules are less flexible, like blue collar workers or healthcare workers. Again, more research is needed, especially with HR professionals like you, since a lot of these changes will be implemented through HR functions. You are at the front line of making sure that it works as planned, taking feedback, and continuously shaping the practice.

I’m learning a lot about HR practices, and I was wondering if you could give examples of programs you have implemented to promote workplace mental health. 

LL:  One of our most important programs is the Johns Hopkins Employee Assistance Program (JHEAP), which provides confidential counseling, resources, and referrals to employees and their families for personal and work-related issues. And we’ve implemented flexible work arrangements. Hybrid or modified hybrid schedules allow employees to meet the needs of their roles and divisions while still managing their personal and work lives. 

We also provide programs that can help employees manage their physical, emotional, social, and financial well-being, like meditation and yoga classes; premium memberships to tools that reduce stress and improve focus, like the Calm app; and the Healthy at Hopkins Wellness Initiative hub for resources and benefits.

Our leadership trainings raise awareness of mental health and unconscious bias and help supervisors recognize and manage employee stress. To reduce the stigma of talking about mental health, we regularly coach managers on how to create open dialogue with their employees about issues like stress and workloads. Through these kinds of initiatives, we want to help managers create a psychologically safe work environment. 

AZ:  Offering a variety of programs is great for addressing individuals’ different needs and creating psychologically safe relationships, while also caring about the overall work environment. Of all these different programs, what has worked well? 

LL:  Our Employee Assistance Program has evolved over the years. The University has been good at adapting it as work set-ups change and employee needs change, so that flexibility has led to a lot of reinventions over the years. Being flexible with our employees’ work arrangements has also worked really well. Everyone is dealing with day-to-day issues and unpredictable situations, so we want managers to balance knowing what needs to be done with caring for their employees. 

JHU’s supervisor trainings have helped managers lead fairly, create open communication, and provide timely feedback so that employees always know where they stand. We also think it’s important to show employees appreciation and recognition for their hard work.

AZ:  Definitely. We’ve seen in research that lack of recognition negatively affects productivity, performance, and mental well-being. It’s always good to see appreciation and recognition coming from the top down. Are there other workplace mental health topics that HR professionals like you are interested in right now?

LL:  I'm interested in learning more about efforts to reduce stigma and promote open dialogue, especially when it comes to relationships between supervisors and their subordinates. What should organizations look out for when managing that relationship?

AZ:  That's a great question because supervisors play an important role in employee mental health. From the research perspective, we develop specific, reliable, and valid measures to assess supervisor behaviors. The commonly used approach is asking workers to answer questions about the frequency of certain supervisor behaviors, such as rudeness or inattention. Those kinds of behaviors are subtle and sometimes low intensity but can affect people’s well-being if experienced regularly.

It's important to note that sometimes employees’ perceptions might not correspond to the actual behavior of the supervisor. The supervisor might not intentionally be rude, but their behaviors can still be perceived as rudeness or incivility. That's why when we study supervisor behaviors, it's important to calibrate across multiple direct reports of the same supervisor. That's an indication of a pattern of behavior and that action needs to be taken in terms of interventions or training. So, I think it’s important for organizations to continuously gather employees’ perceptions and combine data from multiple sources to get a more accurate reflection of supervisor behaviors. To prevent incivility in the workplace, it's important to build an environment where people are aware of their behavior and are mindful of their impact and talk about mental health.

LL:  Reducing mental health stigma is a major theme. We want to raise awareness of resources and make sure that people get the support they need. But when we start talking about illnesses, we start to trickle into the lines of protected health information and figuring out how to handle that information. We have an office that supports employees who need accommodations, but we are still learning. 

AZ: It’s great that HR is thinking about and prioritizing workplace mental health because that’s not the case everywhere. The research on workplace mental health is also still evolving. I’m doing a review piece with a student about disclosure of mental health conditions and how we can foster more open communication so support can be provided. But there’s still a long way to go. As a researcher, I want to keep providing evidence to help teams like yours who are doing actual implementation and supporting employee health and well-being. 

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Brown School PhD students typically develop an individualized research area through coursework and mentored training opportunities. The Systems Science for Health and Social Equity (SSHSE) doctoral concentration provides an opportunity for students interested in the transdisciplinary field to complete relevant coursework and mentored research. The concentration aims to prepare next-generation public health and social work scholars for the following SSHSE competencies:

• Understand how organizational, community, and healthcare systems contribute to public health as complex systems.
• Apply core systems science principles, such as complexity, feedback, emergence dynamics, evolution, endogeneity, social structures, and interactivity to public health research and intervention design.
• Describe how systems thinking and systems science methods contribute to core research activities of description, prediction, explanation, and causal inference.
• Design studies incorporating systems science tools, such as agent-based modeling, systems dynamics modeling, network analysis, group model building, etc.
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SSHSE Training Opportunities: Concentrators are encouraged to participate in the various systems science training opportunities offered across the university, such as the quarterly meetings of the Systems Science Interest Group (SSIG), the annual Systems Sciences for Social Impact (SSSI) Summer Training Institute, and mentored research opportunities through the various funded transdisciplinary research centers using complex systems approaches, such as the Center for Public Health Systems Science, Center on Social Dynamics and Policy, Social System Design Lab, Center for Mental Health Services Research, Center for Advancing Health Services, Policy, and Economic Research, etc.

Mentored Systems Science Dissertation Research: Concentrators identify faculty mentors whose scholarship involved systems science. Typically, these faculty will supervise the completion of an Area Statement & Qualifying Exam. After finishing SSHSE and other required doctoral coursework and milestones, students conduct dissertation research in systems science under the mentorship of faculty working in the area.

Process: Students interested in the concentration work with their faculty advisor, the SSHSE Lead Faculty, and their Program Director to ensure interest alignment. The student and faculty develop and execute research that culminates in a dissertation that contributes to the systems science literature. The successful defense of the SSHSE dissertation is recorded in the student’s final academic transcript.

A team of faculty across Schools coordinates to support SSHSE concentrators. Dr. Douglas Luke, Irving Louis Horowitz Professor in Social Policy, member of the Institute for Public Health, Director of Evaluation for the Institute of Clinical and Translational Science, and founding member of the Washington University Network of Dissemination and Implementation Science Researchers serves as the Concentration Lead. Feel free to reach out with questions and suggestions. Other instructional faculty include:

Douglas Luke PhD, MA Irving Louis Horowitz Professor in Social Policy

• Phone: 314-935-3704
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• Phone: 314-935-2223
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Explaining research performance: investigating the importance of motivation

• Original Paper
• Open access
• Published: 23 May 2024
• Volume 4 , article number  105 , ( 2024 )

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• Silje Marie Svartefoss   ORCID: orcid.org/0000-0001-5072-1293 1   nAff4 ,
• Jens Jungblut 2 ,
• Dag W. Aksnes 1 ,
• Kristoffer Kolltveit 2 &
• Thed van Leeuwen 3  

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In this article, we study the motivation and performance of researchers. More specifically, we investigate what motivates researchers across different research fields and countries and how this motivation influences their research performance. The basis for our study is a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. The analysis shows that researchers are primarily motivated by scientific curiosity and practical application and less so by career considerations. There are limited differences across fields and countries, suggesting that the mix of motivational aspects has a common academic core less influenced by disciplinary standards or different national environments. Linking motivational factors to research performance, through bibliometric data on publication productivity and citation impact, our data show that those driven by practical application aspects of motivation have a higher probability for high productivity. Being driven by career considerations also increases productivity but only to a certain extent before it starts having a detrimental effect.

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Introduction

Motivation and abilities are known to be as important factors in explaining employees’ job performance of employees (Van Iddekinge et al. 2018 ), and in the vast scientific literature on motivation, it is common to differentiate between intrinsic and extrinsic motivation factors (Ryan and Deci 2000 ). In this context, path-breaking individuals are said to often be intrinsically motivated (Jindal-Snape and Snape 2006 ; Thomas and Nedeva 2012 ; Vallerand et al. 1992 ), and it has been found that the importance of these of types of motivations differs across occupations and career stages (Duarte and Lopes 2018 ).

In this article, we address the issue of motivation for one specific occupation, namely: researchers working at universities. Specifically, we investigate what motivates researchers across fields and countries (RQ1) and how this motivation is linked to their research performance (RQ2). The question of why people are motivated to do their jobs is interesting to address in an academic context, where work is usually harder to control, and individuals tend to have a lot of much freedom in structuring their work. Moreover, there have been indications that academics possess an especially high level of motivation for their tasks that is not driven by a search for external rewards but by an intrinsic satisfaction from academic work (Evans and Meyer 2003 ; Leslie 2002 ). At the same time, elements of researchers’ performance are measurable through indicators of their publication activity: their productivity through the number of outputs they produce and the impact of their research through the number of citations their publications receive (Aksnes and Sivertsen 2019 ; Wilsdon et al. 2015 ).

Elevating research performance is high on the agenda of many research organisations (Hazelkorn 2015 ). How such performance may be linked to individuals’ motivational aspects has received little attention. Thus, a better understanding of this interrelation may be relevant for developing institutional strategies to foster environments that promote high-quality research and research productivity.

Previous qualitative research has shown that scientists are mainly intrinsically motivated (Jindal-Snape and Snape 2006 ). Other survey-based contributions suggest that there can be differences in motivations across disciplines (Atta-Owusu and Fitjar 2021 ; Lam 2011 ). Furthermore, the performance of individual scientists has been shown to be highly skewed in terms of publication productivity and citation rates (Larivière et al. 2010 ; Ruiz-Castillo and Costas 2014 ). There is a large body of literature explaining these differences. Some focus on national and institutional funding schemes (Hammarfelt and de Rijcke 2015 ; Melguizo and Strober 2007 ) and others on the research environment, such as the presence of research groups and international collaboration (Jeong et al. 2014 ), while many studies address the role of academic rank, age, and gender (see e.g. Baccini et al. 2014 ; Rørstad and Aksnes 2015 ). Until recently, less emphasis has been placed on the impact of researchers’ motivation. Some studies have found that different types of motivations drive high levels of research performance (see e.g. Horodnic and Zaiţ 2015 ; Ryan and Berbegal-Mirabent 2016 ). However, researchers are only starting to understand how this internal drive relates to research performance.

While some of the prior research on the impact of motivation depends on self-reported research performance evaluations (Ryan 2014 ), the present article combines survey responses with actual bibliometric data. To investigate variation in research motivation across scientific fields and countries, we draw on a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. To investigate how this motivation is linked to their research performance, we map the survey respondents’ publication and citation data from the Web of Science (WoS).

This article is organised as follows. First, we present relevant literature on research performance and motivation. Next, the scientific fields and countries are then presented before elaborating on our methodology. In the empirical analysis, we investigate variations in motivation across fields, gender, age, and academic position and then relate motivation to publications and citations as our two measures of research performance. In the concluding section, we discuss our findings and implications for national decision-makers and individual researchers.

Motivation and research performance

As noted above, the concepts of intrinsic and extrinsic motivation play an important role in the literature on motivation and performance. Here, intrinsic motivation refers to doing something for its inherent satisfaction rather than for some separable consequence. Extrinsic motivation refers to doing something because it leads to a separable outcome (Ryan and Deci 2000 ).

Some studies have found that scientists are mainly intrinsically motivated (Jindal-Snape and Snape 2006 ; Lounsbury et al. 2012 ). Research interests, curiosity, and a desire to contribute to new knowledge are examples of such motivational factors. Intrinsic motives have also been shown to be crucial when people select research as a career choice (Roach and Sauermann 2010 ). Nevertheless, scientists are also motivated by extrinsic factors. Several European countries have adopted performance-based research funding systems (Zacharewicz et al. 2019 ). In these systems, researchers do not receive direct financial bonuses when they publish, although such practices may occur at local levels (Stephan et al. 2017 ). Therefore, extrinsic motivation for such researchers may include salary increases, peer recognitions, promotion, or expanded access to research resources (Lam 2011 ). According to Tien and Blackburn ( 1996 ), both types of motivations operate simultaneously, and their importance vary and may depend on the individual’s circumstances, personal situation, and values.

The extent to which different kinds of motivations play a role in scientists’ performance has been investigated in several studies. In these studies, bibliometric indicators based on the number of publications are typically used as outcome measures. Such indicators play a critical role in various contexts in the research system (Wilsdon et al. 2015 ), although it has also been pointed out that individuals can have different motivations to publish (Hangel and Schmidt-Pfister 2017 ).

Based on a survey of Romanian economics and business administration academics combined with bibliometric data, Horodnic and Zait ( 2015 ) found that intrinsic motivation was positively correlated with research productivity, while extrinsic motivation was negatively correlated. Their interpretations of the results are that researchers motivated by scientific interest are more productive, while researchers motivated by extrinsic forces will shift their focus to more financially profitable activities. Similarly, based on the observation that professors continue to publish even after they have been promoted to full professor, Finkelstein ( 1984 ) concluded that intrinsic rather than extrinsic motivational factors have a decisive role regarding the productivity of academics.

Drawing on a survey of 405 research scientists working in biological, chemical, and biomedical research departments in UK universities, Ryan ( 2014 ) found that (self-reported) variations in research performance can be explained by instrumental motivation based on financial incentives and internal motivation based on the individual’s view of themselves (traits, competencies, and values). In the study, instrumental motivation was found to have a negative impact on research performance: As the desire for financial rewards increase, the level of research performance decreases. In other words, researchers mainly motivated by money will be less productive and effective in their research. Contrarily, internal motivation was found to have a positive impact on research performance. This was explained by highlighting that researchers motivated by their self-concept set internal standards that become a reference point that reinforces perceptions of competency in their environments.

Nevertheless, it has also been argued that intrinsic and extrinsic motivations for publishing are intertwined (Ma 2019 ). According to Tien and Blackburn ( 1996 ), research productivity is neither purely intrinsically nor purely extrinsically motivated. Publication activity is often a result of research, which may be intrinsically motivated or motivated by extrinsic factors such as a wish for promotion, where the number of publications is often a part of the assessment (Cruz-Castro and Sanz-Menendez 2021 ; Tien 2000 , 2008 ).

The negative relationship between external/instrumental motivation and performance and the positive relationship between internal/self-concept motivation and performance are underlined by Ryan and Berbegal-Mirabent ( 2016 ). Drawing on a fuzzy set qualitative comparative analysis of a random sampling of 300 of the original respondents from Ryan ( 2014 ), they find that scientists working towards the standards and values they identify with, combined with a lack of concern for instrumental rewards, contribute to higher levels of research performance.

Based on the above, this article will address two research questions concerning different forms of motivation and the relationship between motivation and research performance.

How does the motivation of researchers vary across fields and countries?

How do different types of motivations affect research performance?

In this study, the roles of three different motivational factors are analysed. These are scientific curiosity, practical and societal applications, and career progress. The study aims to assess the role of these specific motivational factors and not the intrinsic-extrinsic distinction more generally. Of the three factors, scientific curiosity most strongly relates to intrinsic motivation; practical and societal applications also entail strong intrinsic aspects. On the other hand, career progress is linked to extrinsic motivation.

In addition to variation in researchers’ motivations by field and country, we consider differences in relation to age, position and gender. Additionally, when investigating how motivation relates to scientific performance we control for the influence of age, gender, country and funding. These are dimensions where differences might be found in motivational factors given that scientific performance, particularly publication productivity, has been shown to differ along these dimensions (Rørstad and Aksnes 2015 ).

Research context: three fields, five countries

To address the research question about potential differences across fields and countries, the study is based on a sample consisting of researchers in three different fields (cardiology, economics, and physics) and five countries (Denmark, Norway, Sweden, the Netherlands, and the UK). Below, we describe this research context in greater detail.

The fields represent three different domains of science: medicine, social sciences, and the natural sciences, where different motivational factors may be at play. This means that the fields cover three main areas of scientific investigations: the understanding of the world, the functioning of the human body, and societies and their functions. The societal role and mission of the fields also differ. While a primary aim of cardiology research and practice is to reduce the burden of cardiovascular disease, physics research may drive technology advancements, which impacts society. Economics research may contribute to more effective use of limited resources and the management of people, businesses, markets, and governments. In addition, the fields also differ in publication patterns (Piro et al. 2013 ). The average number of publications per researcher is generally higher in cardiology and physics than in economics (Piro et al. 2013 ). Moreover, cardiologists and physicists mainly publish in international scientific journals (Moed 2005 ; Van Leeuwen 2013 ). In economics, researchers also tend to publish books, chapters, and articles in national languages, in addition to international journal articles (Aksnes and Sivertsen 2019 ; van Leeuwen et al. 2016 ).

We sampled the countries with a twofold aim. On the one hand, we wanted to have countries that are comparable so that differences in the development of the science systems, working conditions, or funding availability would not be too large. On the other hand, we also wanted to assure variation among the countries regarding these relevant framework conditions to ensure that our findings are not driven by a specific contextual condition.

The five countries in the study are all located in the northwestern part of Europe, with science systems that are foremost funded by block grant funding from the national governments (unlike, for example, the US, where research grants by national funding agencies are the most important funding mechanism) (Lepori et al. 2023 ).

In all five countries, the missions of the universities are composed of a blend of education, research, and outreach. Furthermore, the science systems in Norway, Denmark, Sweden, and the Netherlands have a relatively strong orientation towards the Anglo-Saxon world in the sense that publishing in the national language still exists, but publishing in English in internationally oriented journals in which English is the language of publications is the norm (Kulczycki et al. 2018 ). These framework conditions ensure that those working in the five countries have somewhat similar missions to fulfil in their professions while also belonging to a common mainly Anglophone science system.

However, in Norway, Denmark, Sweden, and the Netherlands, research findings in some social sciences, law, and the humanities are still oriented on publishing in various languages. Hence, we avoided selecting the humanities field for this study due to a potential issue with cross-country comparability (Sivertsen 2019 ; Sivertsen and Van Leeuwen 2014 ; Van Leeuwen 2013 ).

Finally, the chosen countries vary regarding their level of university autonomy. When combining the scores for organisational, financial, staffing, and academic autonomy presented in the latest University Autonomy in Europe Scorecard presented by the European University Association (EUA), the UK, the Netherlands, and Denmark have higher levels of autonomy compared to Norway and Sweden, with Swedish universities having less autonomy than their Norwegian counterparts (Pruvot et al. 2023 ). This variation is relevant for our study, as it ensures that our findings are not driven by response from a higher education system with especially high or low autonomy, which can influence the motivation and satisfaction of academics working in it (Daumiller et al. 2020 ).

Data and methods

The data used in this article are a combination of survey data and bibliometric data retrieved from the WoS. The WoS database was chosen for this study due to its comprehensive coverage of research literature across all disciplines, encompassing the three specific research areas under analysis. Additionally, the WoS database is well-suited for bibliometric analyses, offering citation counts essential for this study.

Two approaches were used to identify the sample for the survey. Initially, a bibliometric analysis of the WoS using journal categories (‘Cardiac & cardiovascular systems’, ‘Economics’, and ‘Physics’) enabled the identification of key institutions with a minimum number of publications within these journal categories. Following this, relevant organisational units and researchers within these units were identified through available information on the units’ webpages. Included were employees in relevant academic positions (tenured academic personnel, post-docs, and researchers, but not PhD students, adjunct positions, guest researchers, or administrative and technical personnel).

Second, based on the WoS data, people were added to this initial sample if they had a minimum number of publications within the field and belonged to any of the selected institutions, regardless of unit affiliation. For economics, the minimum was five publications within the selected period (2011–2016). For cardiology and physics, where the individual publication productivity is higher, the minimum was 10 publications within the same period. The selection of the minimum publication criteria was based on an analysis of publication outputs in these fields between 2011 and 2016. The thresholds were applied to include individuals who are more actively engaged in research while excluding those with more peripheral involvement. The higher thresholds for cardiology and physics reflect the greater frequency of publications (and co-authorship) observed in these fields.

The benefit of this dual-approach strategy to sampling is that we obtain a more comprehensive sample: the full scope of researchers within a unit and the full scope of researchers that publish within the relevant fields. Overall, 59% of the sample were identified through staff lists and 41% through the second step involving WoS data.

The survey data were collected through an online questionnaire first sent out in October 2017 and closed in December 2018. In this period, several reminders were sent to increase the response rate. Overall, the survey had a response rate of 26.1% ( N  = 2,587 replies). There were only minor variations in response rates between scientific fields; the variations were larger between countries. Tables  1 and 2 provide an overview of the response rate by country and field.

Operationalisation of motivation

Motivation was measured by a question in the survey asking respondents what motivates or inspires them to conduct research, of which three dimensions are analysed in the present paper. The two first answer categories were related to intrinsic motivation (‘Curiosity/scientific discovery/understanding the world’ and ‘Application/practical aims/creating a better society’). The third answer category was more related to extrinsic motivation (‘Progress in my career [e.g. tenure/permanent position, higher salary, more interesting/independent work]’). Appendix Table A1 displays the distribution of respondents and the mean value and standard deviation for each item.

These three different aspects of motivation do not measure the same phenomenon but seem to capture different aspects of motivation (see Pearson’s correlation coefficients in Appendix Table A2 ). There is no correlation between curiosity/scientific discovery, career progress, and practical application. However, there is a weak but significant positive correlation between career progress and practical application. These findings indicate that those motivated by career considerations to some degrees also are motivated by practical application.

In addition to investigating how researchers’ motivation varies by field and country, we consider the differences in relation to age, position and gender as well. Field of science differentiates between economics, cardiology, physics, and other fields. The country variables differentiate between the five countries. Age is a nine-category variable. The position variable differentiates between full professors, associate professors, and assistant professors. The gender variable has two categories (male or female). For descriptive statistics on these additional variables, see Appendix Table A3 .

Publication productivity and citation impact

To analyse the respondents’ bibliometric performance, the Centre for Science and Technology Studies (CWTS) in-house WoS database was used. We identified the publication output of each respondent during 2011–2017 (limited to regular articles, reviews, and letters). For 16% of the respondents, no publications were identified in the database. These individuals had apparently not published in international journals covered by the database. However, in some cases, the lack of publications may be due to identification problems (e.g. change of names). Therefore, we decided not to include the latter respondents in the analysis.

Two main performance measures were calculated: publication productivity and citation impact. As an indicator of productivity, we counted the number of publications for each individual (as author or co-author) during the period. To analyse the citation impact, a composite measure using three different indicators was used: total number of citations (total citations counts for all articles they have contributed to during the period, counting citations up to and including 2017), normalised citation score (MNCS), and proportion of publications among the 10% most cited articles in their fields (Waltman and Schreiber 2013 ). Here, the MNCS is an indicator for which the citation count of each article is normalised by subject, article type, and year, where 1.00 corresponds to the world average (Waltman et al. 2011 ). Based on these data, averages for the total publication output of each respondent were calculated. By using three different indicators, we can avoid biases or limitations attached to each of them. For example, using the MNCS, a respondent with only one publication would appear as a high impact researcher if this article was highly cited. However, when considering the additional indicator, total citation counts, this individual would usually perform less well.

The bibliometric scores were skewedly distributed among the respondents. Rather than using the absolute numbers, in this paper, we have classified the respondents into three groups according to their scores on the indicators. Here, we have used percentile rank classes (tertiles). Percentile statistics are increasingly applied in bibliometrics (Bornmann et al. 2013 ; Waltman and Schreiber 2013 ) due to the presence of outliers and long tails, which characterise both productivity and citation distributions.

As the fields analysed have different publication patterns, the respondents within each field were ranked according to their scores on the indicators, and their percentile rank was determined. For the productivity measure, this means that there are three groups that are equal in terms of number of individuals included: 1: Low productivity (the group with the lowest publication numbers, 0–33 percentile), 2: Medium productivity (33–67 percentile), and 3: High productivity (67–100 percentile). For the citation impact measure, we conducted a similar percentile analysis for each of the three composite indicators. Then everyone was assigned to one of the three percentile groups based on their average score: 1: Low citation impact (the group with lowest citation impact, 0–33 percentile), 2: Medium citation impact (33–67 percentile), and 3: High citation impact (67–100 percentile), cf. Table  3 . Although it might be argued that the application of tertile groups rather than absolute numbers leads to a loss of information, the advantage is that the results are not influenced by extreme values and may be easier to interpret.

Via this approach, we can analyse the two important dimensions of the respondents’ performance. However, it should be noted that the WoS database does not cover the publication output of the fields equally. Generally, physics and cardiology are very well covered, while the coverage of economics is somewhat lower due to different publication practices (Aksnes and Sivertsen 2019 ). This problem is accounted for in our study by ranking the respondents in each field separately, as described above. In addition, not all respondents may have been active researchers during the entire 2011–2017 period, which we have not adjusted for. Despite these limitations, the analysis provides interesting information on the bibliometric performance of the respondents at an aggregated level.

Regression analysis

To analyse the relationship between motivation and performance, we apply multinomial logistic regression rather then ordered logistic regression because we assume that the odds for respondents belonging in each category of the dependent variables are not equal (Hilbe 2017 ). The implication of this choice of model is that the model tests the probability of respondents being in one category compared to another (Hilbe 2017 ). This means that a reference or baseline category must be selected for each of the dependent variables (productivity and citation impact). Furthermore, the coefficient estimates show how the probability of being in one of the other categories decreases or increases compared to being in the reference category.

For this analysis, we selected the medium performers as the reference or baseline category for both our dependent variables. This enables us to evaluate how the independent variables affect the probability of being in the low performers group compared to the medium performers and the high performers compared to the medium performers.

To evaluate model fit, we started with a baseline model where only types of motivations were included as independent variables. Subsequently, the additional variables were introduced into the model, and based on measures for model fit (Pseudo R 2 , -2LL, and Akaike Information Criterion (AIC)), we concluded that the model with all additional variables included provides the best fit to the data for both the dependent variables (see Appendix Tables A5 and A6 ). Additional control variables include age, gender, country, and funding. We include these variables as controls to obtain robust effects of motivation and not effects driven by other underlying factors. The type of funding was measured by variables where the respondent answered the following question: ‘How has your research been funded the last five years?’ The funding variable initially consisted of four categories: ‘No source’, ‘Minor source’, ‘Moderate source’, and ‘Major source’. In this analysis, we have combined ‘No source’ and ‘Minor source’ into one category (0) and ‘Moderate source’ and ‘Major source’ into another category (1). Descriptive statistics for the funding variables are available in Appendix Table A4 . We do not control for the influence of field due to how the scientific performance variables are operationalised, the field normalisation implies that there are no variations across fields. We also do not control for position, as this variable is highly correlated with age, and we are therefore unable to include these two variables in the same model.

The motivation of researchers

In the empirical analysis, we first investigate variation in motivation and then relate it to publications and citations as our two measures of research performance.

As Fig.  1 shows, the respondents are mainly driven by curiosity and the wish to make scientific discoveries. This is by far the most important motivation. Practical application is also an important source of motivation, while making career progress is not identified as being very important.

Motivation of researchers– percentage

As Table  4 shows, at the level of fields, there are no large differences, and the motivational profiles are relatively similar. However, physicists tend to view practical application as somewhat less important than cardiologists and economists. Moreover, career progress is emphasised most by economists. Furthermore, as table 5 shows, there are some differences in motivation between countries. For curiosity/scientific discovery and practical application, the variations across countries are minor, but researchers in Denmark tend to view career progress as somewhat more important than researchers in the other countries.

Furthermore, as table 6 shows, women seem to view practical application and career progress as a more important motivation than men; these differences are also significant. Similar gender disparities have also been reported in a previous study (Zhang et al. 2021 ).

There are also some differences in motivation across the additional variables worth mentioning, as Table  7 shows. Unsurprisingly, perhaps, there is a significant moderate negative correlation between age, position, and career progress. This means that the importance of career progress as a motivation seems to decrease with increased age or a move up the position hierarchy.

In the second part of the analysis, we relate motivation to research performance. We first investigate publications and productivity using the percentile groups. Here, we present the results we use using predicted probabilities because they are more easily interpretable than coefficient estimates. For the model with productivity percentile groups as the dependent variable, the estimates for career progress were negative when comparing the medium productivity group to the high productivity group and the medium productivity group to the low productivity group. This result indicates that the probability of being in the high and low productivity groups decreases compared to the medium productivity group as the value of career progress increases, which may point towards a curvilinear relationship between the variables. A similar pattern was also found in the model with the citation impact group as the dependent variable, although it was not as apparent.

As a result of this apparent curvilinear relationship, we included quadric terms for career progress in both models, and these were significant. Likelihood ratio tests also show that the models with quadric terms included have a significant better fit to the data. Furthermore, the AIC was also lower for these models compared to the initial models where quadric terms were not included (see Appendix Tables A5 – A7 ). Consequently, we base our results on these models, which can be found in Appendix Table A7 . Due to a low number of respondents in the low categories of the scientific curiosity/discovery variable, we also combined the first three values into one to include it as a variable in the regression analysis, which results in a reduced three-value variable for scientific curiosity/discovery.

Results– productivity percentile group

Using the productivity percentile group as the dependent variable, we find that the motivational aspects of practical application and career progress have a significant effect on the probability of being in the low, medium, or high productivity group but not curiosity/scientific discovery. In Figs.  2 and 3 , each line represents the probability of being in each group across the scale of each motivational aspect.

Predicted probability for being in each of the productivity groups according to the value on the ‘practical application’ variable

Predicted probability of being in the low and high productivity groups according to the value on the ‘progress in my career’ variable

Figure  2 shows that at low values of application, there are no significant differences between the probability of being in either of the groups. However, from around value 3 of application, the differences between the probability of being in each group increases, and these are also significant. As a result, we concluded that high scores on practical application is related to increased probability of being in the high productivity group.

In Fig.  3 , we excluded the medium productivity group from the figure because there are no significant differences between this group and the high and low productivity group. Nevertheless, we found significant differences between the low productivity and the high productivity group. Since we added a quadric term for career progress, the two lines in Fig.  3 have a curvilinear shape. Figure  3 shows that there are only significant differences between the probability of being in the low or high productivity group at mid and high values of career progress. In addition, the probability of being in the high productivity group is at its highest value at mid values of career progress. This indicates that being motivated by career progress increases the probability of being in the high productivity group but only up to a certain point before it begins to have a negative effect on the probability of being in this group.

We also included age and gender as variables in the model, and Figs.  4 and 5 show the results. Figure  4 shows that age especially impacts the probability of being in the high productivity and low productivity groups. The lowest age category (< 30–34 years) has the highest probability for being in the low productivity group, while from the mid age category (50 years and above), the probability is highest for being in the high productivity group. This means that increased age is related to an increased probability of high productivity. The variable controlling for the effect of funding also showed some significant results (see Appendix Table A7 ). The most relevant finding is that receiving competitive grants from external public sources had a very strong and significant positive effect on being in the high productivity group and a medium-sized significant negative effect on being in the low productivity group. This shows that receiving external funding in the form of competitive grants has a strong effect on productivity.

Predicted probability of being in each of the productivity groups according to age

Figure  5 shows that there is a difference between male and female respondents. For females, there are no differences in the probability of being in either of the groups, while males have a higher probability of being in the high productivity group compared to the medium and low productivity groups.

Results– citation impact group

For the citation impact group as the dependent variable, we found that career progress has a significant effect on the probability of being in the low citation impact group or the high citation group but not curiosity/scientific discovery or practical application. Figure  6 shows how the probability of being in the high citation impact group increases as the value on career progress increases and is higher than that of being in the low citation impact group, but only up to a certain point. This indicates that career progress increases the probability of being in the high citation impact group to some degree but that too high values are not beneficial for high citation impact. However, it should also be noted that the effect of career progress is weak and that it is difficult to conclude on how very low or very high values of career progress affect the probability of being in the two groups.

Predicted probability for being in each of the citation impact groups according to the value on the ‘progress in my career’ variable

We also included age and gender as variables in the model, and we found a similar pattern as in the model with productivity percentile group as the dependent variable. However, the relationship between the variables is weaker in this model with the citation impact group as the dependent variable. Figure  7 shows that the probability of being in the high citation impact group increases with age, but there is no significant difference between the probability of being in the high citation impact group and the medium citation impact group. We only see significant differences when each of these groups is compared to the low citation impact group. In addition, the increase in probability is more moderate in this model.

Predicted probability of being in each of the citation impact groups according to age

Figure  8 shows that there are differences between male and female respondents. Male respondents have a significant higher probability of being in the medium or high citation impact group compared to the low citation impact group, but there is no significant difference in the probability between the high and medium citation impact groups. For female respondents, there are no significant differences. Similarly, for age, the effect also seems to be more moderate in this model compared to the model with productivity percentile groups as the dependent variable. In addition, the effect of funding sources is more moderate on citation impact compared to productivity (see Appendix Table A7 ). Competitive grants from external public sources still have the most relevant effect, but the effect size and level of significance is lower than for the model where productivity groups are the dependent variable. Respondents who received a large amount of external funding through competitive grants are more likely to be highly cited, but the effect size is much smaller, and the result is only significant at p  < 0.1. Those who do not receive much funding from this source are more likely to be in the low impact group. Here, the effect size is large, and the coefficient is highly significant.

Predicted probability for being in each of the citation impact groups according to gender

Concluding discussion

This article aimed to explore researchers’ motivations and investigate the impact of motivation on research performance. By addressing these issues across several fields and countries, we provided new evidence on the motivation and performance of researchers.

Most researchers in our large-N survey found curiosity/scientific discovery to be a crucial motivational factor, with practical application being the second most supported aspect. Only a smaller number of respondents saw career progress as an important inspiration to conduct their research. This supports the notion that researchers are mainly motivated by core aspects of academic work such as curiosity, discoveries, and practical application of their knowledge and less so by personal gains (see Evans and Meyer 2003 ). Therefore, our results align with earlier research on motivation. In their interview study of scientists working at a government research institute in the UK, Jindal-Snape and Snape ( 2006 ) found that the scientists were typically motivated by the ability to conduct high quality, curiosity-driven research and de-motivated by the lack of feedback from management, difficulty in collaborating with colleagues, and constant review and change. Salaries, incentive schemes, and prospects for promotion were not considered a motivator for most scientists. Kivistö and colleagues ( 2017 ) also observed similar patterns in more recent survey data from Finnish academics.

As noted in the introduction, the issue of motivation has often been analysed in the literature using the intrinsic-extrinsic distinction. In our study, we have not applied these concepts directly. However, it is clear that the curiosity/scientific discovery item should be considered a type of intrinsic motivation, as it involves performing the activity for its inherent satisfaction. Moreover, the practical application item should probably be considered mainly intrinsic, as it involves creating a better society (for others) without primarily focusing on gains for oneself. The career progress item explicitly mentions personal gains such as position and higher salary and is, therefore, a type of extrinsic motivation. This means that our results support the notion that there are very strong elements of intrinsic motivation among researchers (Jindal-Snape and Snape 2006 ).

When analysing the three aspects of motivation, we found some differences. Physicists tend to view practical application as less important than researchers in the two other fields, while career progress was most emphasised by economists. Regarding country differences, our data suggest that career progress is most important for researchers in Denmark. Nevertheless, given the limited effect sizes, the overall picture is that motivational factors seem to be relatively similar regarding disciplinary and country dimensions.

Regarding gender aspects of motivation, our data show that women seem to view practical application and career progress as more important than men. One explanation for this could be the continued gender differences in academic careers, which tend to disadvantage women, thus creating a greater incentive for female scholars to focus on and be motivated by career progress aspects (Huang et al. 2020 ; Lerchenmueller and Sorenson 2018 ). Unsurprisingly, respondents’ age and academic position influenced the importance of different aspects of motivation, especially regarding career progress. Here, increased age and moving up the positional hierarchy are linked to a decrease in importance. This highlights that older academics and those in more senior positions drew more motivation from other sources that are not directly linked to their personal career gains. This can probably be explained by the academic career ladder plateauing at a certain point in time, as there are often no additional titles and very limited recognition beyond becoming a full professor. Finally, the type of funding that scholars received also had an influence on their productivity and, to a certain extent, citation impact.

Overall, there is little support that researchers across various fields and countries are very different when it comes to their motivation for conducting research. Rather, there seems to be a strong common core of academic motivation that varies mainly by gender and age/position. Rather than talking about researchers’ motivation per se, our study, therefore, suggests that one should talk about motivation across gender, at different stages of the career, and, to a certain degree, in different fields. Thus, motivation seems to be a multi-faceted construct, and the importance of different aspects of motivation vary between different groups.

In the second step of our analysis, we linked motivation to performance. Here, we focused on both scientific productivity and citation impact. Regarding the former, our data show that both practical application and career progress have a significant effect on productivity. The relationship between practical application aspects and productivity is linear, meaning that those who indicate that this aspect of motivation is very important to them have a higher probability of being in the high productivity group. The relationship between career aspects of motivation and productivity is curve linear, and we found only significant differences between the high and low productivity groups at mid and high values of the motivation scale. This indicates that being more motivated by career progress increases productivity but only to a certain extent before it starts having a detrimental effect. A common assumption has been that intrinsic motivation has a positive and instrumental effect and extrinsic motivation has a negative effect on the performance of scientists (Peng and Gao 2019 ; Ryan and Berbegal-Mirabent 2016 ). Our results do not generally support this, as motives related to career progress are positively linked with productivity only to a certain point. Possibly, this can be explained by the fact that the number of publications is often especially important in the context of recruitment and promotion (Langfeldt et al. 2021 ; Reymert et al. 2021 ). Thus, it will be beneficial from a scientific career perspective to have many publications when trying to get hired or promoted.

Regarding citation impact, our analysis highlights that only the career aspects of motivation have a significant effect. Similar to the results regarding productivity, being more motivated by career progress increases the probability of being in the high citation impact group, but only to a certain value when the difference stops being significant. It needs to be pointed out that the effect strength is weaker than in the analysis that focused on productivity. Thus, these results should be treated with greater caution.

Overall, our results shed light on some important aspects regarding the motivation of academics and how this translates into research performance. Regarding our first research question, it seems to be the case that there is not one type of motivation but rather different contextual mixes of motivational aspects that are strongly driven by gender and the academic position/age. We found only limited effects of research fields and even less pronounced country effects, suggesting that while situational, the mix of motivational aspects also has a common academic core that is less influenced by different national environments or disciplinary standards. Regarding our second research question, our results challenge the common assumption that intrinsic motivation has a positive effect and extrinsic motivation has a negative effect on the performance of scientists. Instead, we show that motives related to career are positively linked to productivity at least to a certain point. Our analysis regarding citation patterns achieved similar results. Combined with the finding regarding the importance of current academic position and age for specific patterns of motivation, it could be argued that the fact that the number of publications is often used as a measurement in recruitment and promotion makes academics that are more driven by career aspects publish more, as this is perceived as a necessary condition for success.

Our study has a clear focus on the research side of academic work. However, most academics do both teaching and research, which raises the question of how far our results can also inform our knowledge regarding the motivation for teaching. On the one hand, previous studies have highlighted that intrinsic motivation is also of high importance for the quality of teaching (see e.g. Wilkesmann and Lauer 2020 ), which fits well with our findings. At the same time, the literature also highlights persistent goal conflicts of academics (see e.g. Daumiller et al. 2020 ), given that extra time devoted to teaching often comes at the costs of publications and research. Given that other findings in the literature show that research performance continues to be of higher importance than teaching in academic hiring processes (Reymert et al. 2021 ), the interplay between research performance, teaching performance, and different types of motivation is most likely more complicated and demands further investigation.

While offering several relevant insights, our study still comes with certain limitations that must be considered. First, motivation is a complex construct. Thus, there are many ways one could operationalise it, and not one specific understanding so far seems to have emerged as best practice. Therefore, our approach to operationalisation and measurement should be seen as an addition to this broader field of measurement approaches, and we do not claim that this is the only sensible way of doing it. Second, we rely on self-reported survey data to measure the different aspects of motivation in our study. This means that aspects such as social desirability could influence how far academics claim to be motivated by certain aspects. For example, claiming to be mainly motivated by personal career gains may be considered a dubious motive among academics.

With respect to the bibliometric analyses, it is important to realise that we have lumped researchers into categories, thereby ‘smoothening’ the individual performances into group performances under the various variables. This has an effect that some extraordinary scores might have become invisible in our study, which might have been interesting to analyse separately, throwing light on the relationships we studied. However, breaking the material down to the lower level of analysis of individual researchers also comes with a limitation, namely that at the level of the individual academic, bibliometrics tend to become quite sensitive for the underlying numbers, which in itself is then hampered by the coverage of the database used, the publishing cultures in various countries and fields, and the age and position of the individuals. Therefore, the level of the individual academic has not been analysed in our study, how interesting and promising outcomes might have been. even though we acknowledge that such a study could yield interesting results.

Finally, our sample is drawn from northwestern European countries and a limited set of disciplines. We would argue that we have sufficient variation in countries and disciplines to make the results relevant for a broader audience context. While our results show rather small country or discipline differences, we are aware that there might be country- or discipline-specific effects that we cannot capture due to the sampling approach we used. Moreover, as we had to balance sufficient variation in framework conditions with the comparability of cases, the geographical generalisation of our results has limitations.

This article investigated what motivates researchers across different research fields and countries and how this motivation influences their research performance. The analysis showed that the researchers are mainly motivated by scientific curiosity and practical application and less so by career considerations. Furthermore, the analysis shows that researchers driven by practical application aspects of motivation have a higher probability of high productivity. Being driven by career considerations also increases productivity but only to a certain extent before it starts having a detrimental effect.

The article is based on a large-N survey of economists, cardiologists, and physicists in Denmark, Norway, Sweden, the Netherlands, and the UK. Building on this study, future research should expand the scope and study the relationship between motivation and productivity as well as citation impact in a broader disciplinary and geographical context. In addition, we encourage studies that develop and validate our measurement and operationalisation of aspects of researchers’ motivation.

Finally, a long-term panel study design that follows respondents throughout their academic careers and investigates how far their motivational patterns shift over time would allow for more fine-grained analysis and thereby a richer understanding of the important relationship between motivation and performance in academia.

Data availability

The data set for this study is available from the corresponding author upon reasonable request.

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We are thankful to the R-QUEST team for input and comments to the paper.

The authors disclosed the receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Research Council Norway (RCN) [grant number 256223] (R-QUEST).

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Silje Marie Svartefoss

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Silje Marie Svartefoss & Dag W. Aksnes

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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Silje Marie Svartefoss, Jens Jungblut, Dag W. Aksnes, Kristoffer Kolltveit, and Thed van Leeuwen. The first draft of the manuscript was written by all authors in collaboration, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Svartefoss, S.M., Jungblut, J., Aksnes, D.W. et al. Explaining research performance: investigating the importance of motivation. SN Soc Sci 4 , 105 (2024). https://doi.org/10.1007/s43545-024-00895-9

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Maternal employment characteristics as a structural social determinant of breastfeeding after return to work in the European Region: a scoping review

• Pauline Brugaillères 1 ,
• Séverine Deguen 1 ,
• Sandrine Lioret 2 ,
• Sahar Haidar 3 ,
• Corinne Delamaire 3 ,
• Emilie Counil 4 , 5 &
• Stéphanie Vandentorren 1 , 3  

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The European Region has the lowest rate of exclusive breastfeeding at 6 months worldwide. Improving work-related breastfeeding issues is important given that women may have difficulties combining work and breastfeeding, especially those in precarious working situations, which adds to their adversity. This scoping review overviews research on the maternal employment characteristics that support breastfeeding continuation after return to work in the European Region.

Studies published from 2013 to 2023 were collected from Scopus, PubMed, and PsycInfo. Quantitative and qualitative studies published in English or French that explored the association between maternal employment characteristics and any breastfeeding status, duration, or experience were included. Participants included were mothers of healthy children who continued breastfeeding after resuming work. The main determinants were work-related factors that can lead to socially differentiated working conditions, including type of employment (e.g., occupation, employed/self-employed status, type of contract, working time, occupational prestige), working conditions (e.g., work schedule, decision latitude, latitude to organize worktime), and work environment (e.g., occupational exposure, family-friendly workplace policy, social support). The geographic area encompassed countries included in the World Health Organization European Region.

Of the 693 single studies retrieved and screened, 13 were included in the review. Eight studies focused on combining work and breastfeeding, while the others had a broader spectrum by investigating breastfeeding determinants. The represented countries were Spain ( n  = 4), France ( n  = 4), UK ( n  = 2), Ireland ( n  = 2), and the Netherlands ( n  = 1). Results highlighted the heterogeneity of measures, time frames, and fields of inquiry, thus revealing a lack of conceptual framework regarding the links between work, breastfeeding, and social health inequalities. Nonetheless, being self-employed, working in a non-manual profession with time flexibility, having lactation rooms at work, being supported by co-workers, and having a breastfeeding workplace policy were salient factors that supported breastfeeding in working mothers.

Conclusions

Supporting working mothers who choose to breastfeed is important given the myriad of adverse factors faced by mothers and their children. These results advocate for targeted actions at the workplace such as time flexibility, breastfeeding facilities, and the promotion of breastfeeding-friendly policies.

Breastfeeding rates remain relatively low in high-income countries, particularly in the WHO European Region, which has the lowest rates of exclusive breastfeeding in infants aged 6 months compared with other regions, standing at about 25% [ 1 ]. Breastfeeding practices vary substantially across high-income countries and within the European Region [ 2 ]. As revealed by a survey comparing data from 11 European countries, between 56% (Ireland) and 98% (Norway) of infants were reported to receive any human milk after birth; at 6 months, 38% (Italy) to 71% (Norway) of infants were continuing breastfed, while 13% (Denmark) to 39% (Netherlands) were exclusively breastfed [ 3 ]. These cross-national variations in breastfeeding practices may be partially explained by the various social policies in place. Maternity leave regulations differ substantially across the European Region: countries like Sweden, Finland, and Portugal, which offer lengthy and well-compensated maternity leave and have greater uptake, flexibility, and division of leave between parents, show better breastfeeding outcomes in terms of initiation and duration [ 4 ].

Indeed, policy attributes are one of the five types of determinants for successful breastfeeding, together with community, health care-related, psycho-social, and sociodemographic attributes [ 4 ]. According to the conceptual model proposed by the 2016 Lancet Breastfeeding Series, breastfeeding determinants operate from the most distal levels – i.e., sociocultural context, formula milk industry, health system, family or community, and workplace or employment – to the most proximal levels – i.e., individual factors such as mother and infant attributes and mother-infant relationship [ 5 ]. From a socioecological perspective, regulations play the most crucial role in breastfeeding initiation and duration rates such as the existence of baby-friendly hospitals, the international code of marketing for breast-milk substitutes, and maternal, paternal, and parental leave [ 5 , 6 ]. In the workplace, employers have legal obligations toward lactating mothers, although public policies are still needed for working women to effectively support their choice to breastfeed. Moreover, employment is sometimes conceptualized as the relationship between a woman’s productive and reproductive work; because breastfeeding is sex-specific, it challenges the feminist principle of gender-neutral child rearing [ 7 ]. Indeed, the socioecological framework does not take into account how gender is inherently connected with breastfeeding at the structural, cultural, and personal levels such as the place of motherhood in women’s lives, the sexualization versus maternal function of their bodies, and the issue of personal choice [ 4 , 8 ].

Returning to work while still breastfeeding remains the main challenge faced by lactating mothers [ 5 , 9 , 10 ]. Work-related factors include working full-time, not having access to a suitable place to express and store breast milk, not being supported by co-workers, and returning to work earlier, which all impair breastfeeding intention and practices, including initiation and duration [ 5 ]. Removing work-related breastfeeding barriers is especially important given women’s active participation in the labor force. Furthermore, it has been shown that supporting breastfeeding reduces sick leave due to child illness [ 11 ]. In contemporary Western societies, even though breastfeeding is praised particularly for its health benefits, there is considerable cultural stigmatization around the current practice of breastfeeding [ 12 ], and women may face many difficulties when trying to combine work and breastfeeding. This is especially true for women experiencing socioeconomic disadvantage. Indeed, women with low education level are frequently in low-skilled or precarious employment, characterized by non-supportive breastfeeding environments (e.g., manual labor, full-time, lack of flexibility) [ 13 , 14 ].

The macro-theoretical framework proposed by the WHO Commission on Social Determinants of Health gives some insight into the relations between employment and health inequalities [ 15 ] (Additional file 1 ). From this, and with the aim of better supporting working women who choose to breastfeed, the present study proposes a deeper understanding of the work-related factors that may hinder this personal/family choice and that may, in turn, worsen social inequalities in maternal and child health. To our knowledge, no study to date has reviewed the structural social determinants of breastfeeding in Europe such as maternal employment in light of the social inequalities in breastfeeding practices after return to work. To fill this gap, the present scoping review aims to identify the maternal employment characteristics that support any breastfeeding continuation after resuming work in the European Region.

This scoping review was guided by the Joanna Briggs Institute’s approach to scoping reviews [ 16 ] and compliant with the PRISMA-ScR checklist [ 17 ].

Inclusion criteria

Full-text peer-reviewed articles using quantitative and/or qualitative methods and published in English or French between 2013 and 2023 were included according to the following inclusion criteria: (1) Population: mothers of a healthy child with an experience of breastfeeding after resuming work; (2) Outcomes: any breastfeeding duration (i.e., exclusive, predominant, or partial), breastfeeding status, or breastfeeding experience after returning to work; (3) Main determinants: any maternal employment factors that can lead to socially differentiated working conditions, including organizational aspects such as work type, work schedule, worktime flexibility, or type of contract as well as environmental factors like occupational exposure, arduousness, or social support at work; (4) Geographic coverage of the study: countries in the WHO European Region.

Exclusion criteria

Articles based on interventional studies, opinion pieces, editorials, case studies, or any types of reviews were excluded. Since we focused on mothers choosing to combine breastfeeding and work, studies that only reported associations between breastfeeding practices and maternity leave duration or return to work timeframe were excluded. For the same reason, we also excluded studies focusing solely on breastfeeding intention or initiation, which are events that occur upstream of the return to work. Finally, we excluded studies that only investigated employment as a dichotomous variable (i.e., working vs not working).

Search strategy

Three electronic databases were used, including Scopus, PubMed, and PsycInfo for relevant articles published in the past 10 years (database searches were conducted on October 22, 2022, and updated on March 20, 2023). The search strategy was first developed in Scopus using proximity operators (e.g., W/3 means that two keywords of interest must be within a maximum distance of three words) and was as follows: (TITLE (Breastf* OR "Breast F*" OR (mother* W/3 milk) OR "Infant Feeding") AND (TITLE-ABS-KEY(((*employ* OR work* OR occupation* OR Job) W/3 (mother OR maternal OR women)) OR "work related" OR "Occupation* related" OR Workplace OR ((parental OR matern* OR Mother OR Breastf* OR "Breast F*") W/3 leave) OR ((job OR Work* OR *employ* OR Occupation*) W/3 (characteristic OR Status OR condition OR Schedule)) OR Shift-work* OR Shiftwork OR "return* to work" OR self-employed) OR KEY("Women Working"))). This search was then adapted to each of the different databases (Additional file 2 ).

After eliminating duplicates, P.B. screened all titles and abstracts using a priori eligibility criteria (e.g., type of paper, country, targeted population, breastfeeding outcome). Then P.B. read the full-text articles of the remaining references to confirm their eligibility; a double-check was carried out at 20% by S.D. ( n  = 17/87; 89% agreement), with any conflicts being resolved by a third reviewer (S.V.).

Data synthesis and analysis

For each study, data were extracted and summarized in several tables. The following information was reported:

General information concerning the author’s name, country, and study date;

Main study characteristics: study design, period, location, statistical methods, and population size;

Participant characteristics including information on confounders;

Work-related factors considered to support (or not) breastfeeding when returning to work;

Outcome definitions including any, exclusive, or predominant breastfeeding;

Main findings concerning assessments of association, including odds ratios (ORs), hazard ratios (HRs), relative risks (RRs), and other metrics measuring the strength of association of maternal employment characteristics with breastfeeding duration, employment status after returning to work, and experience of breastfeeding as reported in qualitative studies (e.g., work-related barriers and facilitators).

When several measures of association were available for a given outcome, we reported those from the fully adjusted models.

Description of maternal work-related variables

We grouped the work-related variables into three main dimensions described as follows:

Type of employment refers to the terms that govern the organization of work, generally stated in the contract between the employer and employee, and includes the occupation, work status (employed/self-employed), type of contract (permanent/fixed-term/temporary), working time (part-time/full-time) and occupational prestige (manual/non-manual).

Working conditions refers to the constraint level to which workers are subject and includes work schedule (atypical/regular shift), decision latitude, and latitude to organize worktime (onsite/teleworking/hybrid/flexible hours).

Work environment is generally not defined by the contract but includes occupational exposure and hazards (e.g., chemical, physical), family-friendly breastfeeding workplace policies such as workplace facilities (e.g., lactation room, childcare system) and social network characteristics (e.g., parity, social support from manager or colleagues).

Study selection

A total of 856 articles were selected from the three databases (Fig.  1 ). After removing duplicates ( n  = 163), 693 articles were screened for possible relevance based on their title and abstract. A total of 87 studies met our inclusion criteria and were subject to a full-text review, with 13 articles meeting the eligibility criteria and being included in this scoping review.

PRISMA flow diagram of study selection

Characteristics of the included studies

Table 1 provides an overview of the included studies: in eight of the articles, the relation between maternal work and breastfeeding practices was main objective [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ], while the remaining five investigated a broader spectrum of determinants [ 26 , 27 , 28 , 29 , 30 ]. The majority of studies were conducted in Spain ( n  = 4) and France ( n  = 4), followed by the UK ( n  = 2), Ireland ( n  = 2), and the Netherlands ( n  = 1). Eight studies were conducted on mothers sampled from the general population, whereas the others targeted mothers working at a university ( n  = 3) or immigrant mothers (Latina [ n  = 1] or Chinese [ n  = 1]). Eight studies were quantitative, and five were qualitative. There was thus substantial heterogeneity between the available studies.

Factors related to the type of employment

A previous study revealed that compared with managers, self-employed mothers were twice as likely to combine breastfeeding and work (OR 95% CI 2.2 (1.1, 4.5)), while intermediate professionals (OR 95% CI 0.6 (0.4, 0.8)) and manual workers (OR 95% CI 0.5 (0.3, 0.9)) were less likely to combine breastfeeding and work [ 22 ]. Accordingly, Villar et al. observed higher rates of predominant breastfeeding at 13 or 16 weeks in non-manual working mothers (59 and 52%, respectively) compared with their manual counterparts (48 and 41%, respectively). However, the likelihood of breastfeeding cessation did not differ between manual and non-manual workers in the fully adjusted model (not adjusted for child’s age) [ 27 ]. Inconsistent results were found concerning the association between working time and breastfeeding. Data from a French birth cohort revealed that working part-time during the first year postpartum was associated with longer breastfeeding duration [ 19 ]. This was especially true for primiparous mothers who were more likely to breastfeed for at least 9 months compared with an intermediate duration of 3 to < 6 months when they shifted from full-time work during pregnancy to part-time work in the first year postpartum (OR 95% CI 1.8 (1.2, 2.7)). However, other studies did not observe significant differences in breastfeeding duration [ 23 , 24 ] or breastfeeding rate at 4 months [ 21 ] depending on the work schedules (part-time vs full-time).

Factors related to the work conditions

Zilanawala et al. investigated maternal nonstandard work schedules and breastfeeding duration: no differences in the odds of breastfeeding duration patterns (i.e., less than 2 months, between 2 and 4 months, more than 4 months) were shown in terms of mothers’ nonstandard working schedules (i.e., working evenings, nights, or weekend shifts) in the fully adjusted models [ 25 ]. Lack of time or flexibility to express milk at work was cited by mothers as a barrier to breastfeeding in several qualitative studies [ 20 , 23 , 30 ] but also discussed as a potential explanatory factor of deleterious breastfeeding outcomes in other studies, which nevertheless did not measure lack of time or flexibility [ 18 , 19 , 21 , 22 ]. Only two studies [ 18 , 24 ] targeting Spanish mothers working at universities have quantitatively measured the ‘Break Time’ dimension using the Workplace Breastfeeding Support Scale (WBSS) [ 31 ]. This dimension measures, for example, mothers’ perception of the frequency and duration of their break time (e.g., “My breaks are frequent/long enough for breastfeeding or pumping breast milk”) but also their time flexibility (“I can adjust my break schedule in order to breastfeed or pump breast milk”) on a 7-point Likert scale. Both studies showed that compared with administrative staff, faculty members took more breastfeeding breaks and were able to organize their breaks more easily. Faculty members were also more likely to continue breastfeeding after returning to work [ 24 ]. However, in these studies, the ‘Break Time’ dimension was not assessed according to breastfeeding outcomes.

Factors related to the work environment

Working environment factors were systematically highlighted in qualitative studies exploring nursing mothers’ experiences [ 20 , 23 , 26 , 29 , 30 ]. The cited breastfeeding facilitators were mostly related to the possibility and ease for mothers to express milk during working hours: availability of adequate breastfeeding facilities (i.e., quiet lactation room with cleaning and storage facilities) [ 18 , 23 , 29 ] or the existence of childcare near the workplaces [ 30 ]. In their quantitative study, Leon-Larios et al. showed that compared with administrative staff, faculty members had easier access to quiet places to pump breast milk and breastfed for longer (association between access to pumping room and breastfeeding duration not assessed) [ 24 ]. Broadly, the workplace breastfeeding policy seems to play a major role: as reported by a French study, women were more likely to breastfeed for more than 4 months when their workplace had implemented a breastfeeding-friendly policy (OR 95% CI 1.8 (1.1, 2.8)), fully adjusted model) compared with those which did not [ 28 ]. When comparing breastfeeding duration between two universities with contrasting breastfeeding policies, Cervera-Gasch et al. highlighted that the factors associated with longer breastfeeding were the university having a breastfeeding support policy and special breastfeeding facilities; participating in breastfeeding support groups; intending to continue breastfeeding after returning to work; knowing the occupational legislation in force; and having a female supervisor [ 18 ]. In line with the latter, the negative attitude of managers and colleagues, the perceived lack of support from them, the difficulty of asking for time to express in the workplace, especially in male-dominated environments, and the stress caused by male gazing were all breastfeeding barriers identified by working mothers [ 20 , 26 ].

This scoping review aimed to identify maternal employment characteristics that support any breastfeeding continuation when returning to work in the WHO European Region. To better highlight the characteristics of employment that can lead to social inequalities, we proposed a classification through three main dimensions: type of employment, working conditions, and work environment. While these dimensions are interrelated, our review highlights that no study to date has combined all three dimensions in their measured variables. Furthermore, there is a large heterogeneity of measured work-related and breastfeeding variables, time frames, and fields of inquiry, thus revealing the lack of a conceptual framework for the links between work, breastfeeding, and social health inequalities. Nevertheless, it appears that being self-employed or working in a non-manual occupation with time flexibility, the availability of breastfeeding facilities at work, the support of co-workers, and the existence of a breastfeeding workplace policy are salient factors that promote breastfeeding among working mothers. These results are interpreted in Fig.  2 .

Maternal employment characteristics that support any breastfeeding continuation when returning to work in European countries. Maternal employment characteristics were grouped into three main dimensions. The type of employment dimension refers to the terms that govern the organization of work, generally stated in the contract between the employer and employee. The working conditions dimension refers to the level of constraints to which workers are subjected. The work environment dimension pertains to factors generally not defined by the contract (e.g., family-friendly breastfeeding workplace policies, occupational exposure, social network)

Being self-employed implies a high level of autonomy with an early return to work. This work status was associated with longer breastfeeding duration in France [ 22 ]. As emphasized by authors, the autonomy inherent in the self-employed status can be seen as a factor favoring flexibility and thus the continuation of breastfeeding. Nevertheless, it also implies a greater dedication to work and less institutional support, which would affect the initiation of breastfeeding. A longitudinal Australian cohort study illustrated this duality by showing that women in occupations with higher levels of autonomy and limited hazards (e.g., exposure to extreme noise, temperature levels, chemicals) were more likely to intend to breastfeed and initiate it [ 32 ]. Unfortunately, in the articles identified by this scoping review, occupational exposure was neither measured nor investigated. Finally, it appears that non-manual jobs positively influence breastfeeding [ 28 , 33 ]. These working mothers from socially advantaged backgrounds and with higher education levels probably have a higher degree of health awareness, better health literacy, greater autonomy over their work schedule, more resources to seek help, and better compliance with the existing recommendations [ 33 , 34 ]. In agreement, breastfeeding surveys conducted in 19 European countries showed that a low education level is associated with a lower initiation of breastfeeding and earlier weaning [ 35 ]. As underlined by several European studies, the promotion, protection, and support of breastfeeding should be provided to all breastfeeding mothers, with specific interventions tailored to the more disadvantaged groups such as young and less educated mothers [ 23 , 33 , 35 , 36 ]. Alternative explanations could be that manual working mothers are more likely to stop breastfeeding when resuming work than their non-manual counterparts, so as not to add to the stress or fatigue of their already physically demanding job. As stressed by Rollins et al., the impact of work on breastfeeding is multidimensional, including fatigue and practicality [ 5 ]. A French survey conducted on 1,000 women showed that breast pain, fatigue, and back pain were the main difficulties encountered during breastfeeding [ 37 ].

In terms of the work conditions dimension, the qualitative studies show that worktime flexibility is a major facilitator of breastfeeding continuation. Having the freedom to organize their own working time can potentially increase breastfeeding mothers’ capability, which refers to whether people have the knowledge, skills, and abilities required to engage in a particular behavior. Based on the framework of behavior change by Michie et al., capability influences motivation, which plays a major role in breastfeeding practices [ 38 , 39 , 40 ]. A recent Spanish study showed, for example, that women who decided to opt for exclusive breastfeeding and maintain it “as long as I can” were five times more likely to meet their expectations than women who set less ambitious expectations concerning exclusive breastfeeding duration [ 41 ]. Overall, these results highlight that employment may influence the entire breastfeeding process from intention to continuation. Indeed, breastfeeding intention – which is the strongest predictor of breastfeeding initiation and duration – is formed during pregnancy [ 39 , 42 ]. The mother’s choice could be influenced by the anticipation of their expected work-life balance after resuming work [ 43 , 44 ].

Regarding the work environment dimension, the studies summarized here identified a key feature, namely the importance of a set of underlying conditions: organizational (i.e., presence of adequate lactation room, childcare close to the workplace), structural (i.e., breastfeeding policies in the workplace), and even interpersonal conditions (i.e., support from co-workers), which must coexist to allow mothers to express their milk. In line with the interpersonal dimension, it was underlined that female-dominated environments were perceived to be more positive and supportive, thus enhancing breastfeeding practices [ 18 , 23 , 24 ]. A female environment would facilitate communication and shared experiences [ 23 ]. Findings from a study in the US showed that compared with female coworkers, males were more stigmatizing to lactating colleagues, had more responses of disgust, had a poorer perception of the fairness of the additional break time accorded for pumping breast milk, and showed less support [ 45 ]. Recent literature reviews and meta-analysis unanimously pointed out the lack of research on the effectiveness of interventions to support breastfeeding in the workplace in high-income countries, specifically in the European Region [ 46 , 47 , 48 , 49 ]. As demonstrated in 2022 by Tomori et al. in their review of reviews, inadequate attention is given to interventions addressing policy and structural factors, and only 9% addressed workplace intervention settings [ 48 ].

Our results should also be considered according to different national parental leave and return-to-work policies that play a crucial role in influencing breastfeeding practices. The five countries represented in our corpus (i.e., Spain, France, UK, Ireland and the Netherland) have different statutory well-paid maternity leaves durations that vary from 16 weeks (Spain, France and the Netherland) to 39 weeks (UK) whilst paternity leaves durations vary from 1 week (UK and The Netherland) to 16 weeks (Spain) [ 50 ]. Additional parental leaves are generally low or unpaid, inflexible, and not evenly distributed between fathers and mothers, because of the conservative division of gender roles predominant in these countries [ 4 , 51 ]. Conversely, Sweden, which has one of the most generous, supportive and equitable parental leave programs in the world provides some insights into the integration of breastfeeding and women’s employment [ 52 ]. A cross sectional study among Swedish families revealed that a longer period of shared parental leave was associated with an extended duration of breastfeeding [ 53 ]. Thus, from national policy directives to sociocultural attitudes and values, maternal employment conditions play a crucial role to improve breastfeeding.

This study has several limitations. Inherent to the design of scoping reviews, we did not assess the methodological quality of the included papers, and so we only discuss general, albeit, limited findings regarding breastfeeding and maternal employment. This work lacks representativeness, since only five of the 53 countries included in the WHO European Region were represented in our study selection with an exclusive representation of the countries in North-West and Southern Europe. Finally, from a methodological point of view, we observed heterogeneity in the description and analysis of maternal work-related variables, thus making comparisons difficult across studies. As underlined by some authors, data on work characteristics were often limited [ 22 ], and job title classifications should be homogenized throughout the European Region [ 54 ]. While not investigated in our corpus, we may assume that other stressor factors such as job insecurity, occupational exposure to chemicals, and physical strain may also affect breastfeeding practices. Given that some studies from our corpus did not specifically aim to assess the associations between breastfeeding and maternal work, the infant’s age at the time of breastfeeding cessation was not always reported or considered in the adjusted models: this made it difficult to interpret the reason for breastfeeding cessation (e.g., work-related, meeting expectations, duration regarded as sufficient). The strength of this scoping review lies in its innovative approach by considering maternal employment characteristics in light of social inequalities. Broadly, and as conceptualized by the WHO [ 15 ], employment conditions can lead to social health inequalities through numerous behavioral, psychosocial, and physio-pathological pathways: employment conditions (e.g., full-time work, precarious employment) influence working conditions (e.g., physical and chemical hazards, ergonomics, psychosocial), and both are affected by social and family networks, health system, material deprivation, and economic inequalities. The scoping review methodology allowed us to apply a broad research question and iterative search strategy to gain a comprehensive overview of the current literature on maternal work characteristics and breastfeeding as a major public health outcome. Additionally, we considered the association between maternal work characteristics and any types of breastfeeding, without restricting the analysis to exclusive breastfeeding. We believe that this inclusive approach is relevant given the beneficial effects of breastfeeding, even partial, compared with not breastfeeding [ 55 , 56 ].

This review highlights that the pursuit of breastfeeding after returning to work is associated with various work characteristics that act at different interrelated dimensions (i.e., type of employment, working conditions, and work environment). Supporting disadvantaged working mothers who choose to breastfeed is all the more important given the myriad of adverse factors to which underprivileged mother and child dyads are exposed. Results from our review suggest the need for policy directives or workplace interventions to improve employment quality in order to favor work-life balance: targeting low skilled or precarious jobs by increasing flexibility and reorganizing manual work posts to be less stressful could be a relevant perspective to reduce social health inequalities broadly, and in particular, in relation to breastfeeding practices. Widely, promoting work-life balance at this crucial moment of child arrival must address the issue of gender inequalities in domestic labor. This work also advocates for actions at a more macroscopic level with the implementation of well-paid, flexible and equitable parental leave regulations between both parents in Europe. From a methodological perspective, there is an additional need for a rigorous and homogenous assessment of maternal employment characteristics in studies in order to better understand the specificities that mothers face in the workplace – including potential stressors like job insecurity, occupational exposure to chemicals, or physical strain – and to identify targeted actions. Furthermore, better quantifying worktime flexibility in studies could be of interest, since this aspect seems to play a major role in the pursuit of breastfeeding after returning to work. The new working practices adopted since the COVID-19 pandemic have challenged this link between work-life balance and social health inequalities, since precarious employees, including manual workers, are less likely to work from home.

Availability of data and materials

All data generated or analysed during this study are included in this published article [and its supplementary information files].

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Acknowledgements

The authors would like to thank Edwige Bertrand for her help in the bibliographic search strategy.

This study was funded by the French National Research Agency (ANR-19-CE36-0006).

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Additional file 1. Macro-theoretical framework of employment relations and health inequalities from the WHO Commission on Social Determinants of Health (CSDH) Employment Conditions Knowledge Network (EMCONET), Final Report, 20 September 2007.

Additional file 2. Literature Search Strategy.

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Brugaillères, P., Deguen, S., Lioret, S. et al. Maternal employment characteristics as a structural social determinant of breastfeeding after return to work in the European Region: a scoping review. Int Breastfeed J 19 , 38 (2024). https://doi.org/10.1186/s13006-024-00643-y

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Is College Worth It?

1. labor market and economic trends for young adults, table of contents.

• Labor force trends and economic outcomes for young adults
• Economic outcomes for young men
• Economic outcomes for young women
• Wealth trends for households headed by a young adult
• The importance of a four-year college degree
• Getting a high-paying job without a college degree
• Do Americans think their education prepared them for the workplace?
• Is college worth the cost?
• Acknowledgments
• The American Trends Panel survey methodology
• Current Population Survey methodology
• Survey of Consumer Finances methodology

A majority of the nation’s 36 million workers ages 25 to 34 have not completed a four-year college degree. In 2023, there were 19 million young workers who had some college or less education, including those who had not finished high school.

The overall number of employed young adults has grown over the decades as more young women joined the workforce. The number of employed young adults without a college degree peaked around 1990 at 25 million and then started to fall, as more young people began finishing college .

This chapter looks at the following key labor market and economic trends separately for young men and young women by their level of education:

Labor force participation

• Individual earnings

Household income

• Net worth 1

When looking at how young adults are doing in the job market, it generally makes the most sense to analyze men and women separately. They tend to work in different occupations and have different career patterns, and their educational paths have diverged in recent decades.

In 1970, almost all young men whose highest educational attainment was a high school diploma (98%) were in the labor force, meaning they were working or looking for work. By 2013, only 88% of high school-educated young men were in the labor force. Today, that share is 87%.

Similarly, 96% of young men whose highest attainment was some college education were in the labor force in 1970. Today, the share is 89%.

By comparison, labor force participation among young men with at least a bachelor’s degree has remained relatively stable these past few decades. Today, 94% of young men with at least a bachelor’s degree are in the labor force.

The long-running decline in the labor force participation of young men without a bachelor’s degree may be due to several factors, including declining wages , the types of jobs available to this group becoming less desirable, rising incarceration rates and the opioid epidemic . 2

Looking at labor force and earnings trends over the past several decades, it’s important to keep in mind broader forces shaping the national job market.

The Great Recession officially ended in June 2009, but the national job market recovered slowly . At the beginning of the Great Recession in the fourth quarter of 2007, the national unemployment rate was 4.6%. Unemployment peaked at 10.4% in the first quarter of 2010. It was not until the fourth quarter of 2016 that unemployment finally returned to its prerecession level (4.5%).

Studies suggest that things started to look up for less-skilled workers around 2014. Among men with less education, hourly earnings began rising in 2014 after a decade of stagnation. Wage growth for low-wage workers also picked up in 2014. The tightening labor markets in the last five years of the expansion after the Great Recession improved the labor market prospects of “vulnerable workers” considerably.

The COVID-19 pandemic interrupted the tight labor market, but the COVID-19 recession and recovery were quite different from the Great Recession in their job market impact. The more recent recession was arguably more severe, as the national unemployment rate reached 12.9% in the second quarter of 2020. But it was short – officially lasting two months, compared with the 18-month Great Recession – and the labor market bounced back much quicker. Unemployment was 3.3% before the COVID-19 recession; three years later, unemployment had once again returned to that level.

Full-time, full-year employment

Since the Great Recession of 2007-09, young men without a four-year college degree have seen a significant increase in the average number of hours they work.

• Today, 77% of young workers with a high school education work full time, full year, compared with 69% in 2011.
• 83% of young workers with some college education work full time, full year, compared with 70% in 2011.

The share of young men with a college degree who work full time, year-round has remained fairly steady in recent decades – at about 80% – and hasn’t fluctuated with good or bad economic cycles.

Annual earnings

Annual earnings for young men without a college degree were on a mostly downward path from 1973 until roughly 10 years ago (with the exception of a bump in the late 1990s). 3

Earnings have been increasing modestly over the past decade for these groups.

• Young men with a high school education who are working full time, full year have median earnings of $45,000 today, up from $39,300 in 2014. (All figures are in 2022 dollars.)
• The median earnings of young men with some college education who are working full time, full year are $50,000 today, similar to their median earnings in 2014 ($49,100).

It’s important to note that median annual earnings for both groups of noncollege men remain below their 1973 levels.

Median earnings for young men with a four-year college degree have increased over the past 10 years, from $67,500 in 2014 to $77,000 today.

Unlike young men without a college degree, the earnings of college-educated young men are now above what they were in the early 1970s. The gap in median earnings between young men with and without a college degree grew significantly from the late 1970s to 2014. In 1973, the typical young man with a degree earned 23% more than his high school-educated counterpart. By 2014, it was 72% more. Today, that gap stands at 71%. 4

Household income has also trended up for young men in the past 10 years, regardless of educational attainment.

This measure takes into account the contributions of everyone in the household. For this analysis, we excluded young men who are living in their parents’ home (about 20% of 25- to 34-year-old men in 2023).

• The median household income of young men with a high school education is $75,200 today, up from $63,800 in 2014. This is slightly lower than the highpoint reached around 2019.
• The median household income of young men with some college education is $92,200 today, up from $81,100 in 2014. This is close to the 2022 peak of $93,800.

The median household income of young men with at least a bachelor’s degree has also increased from a low point of $118,700 in 2014 after the Great Recession to $145,000 today.

The gap in household income between young men with and without a college degree grew significantly between 1980 and 2014. In 1980, the median household income of young men with at least a bachelor’s degree was about 38% more than that of high school graduates. By 2014, that gap had widened to 86%.

Over the past 10 years, the income gap has fluctuated. In 2023, the typical college graduate’s household income was 93% more than that of the typical high school graduate.

The 2001 recession and Great Recession resulted in a large increase in poverty among young men without a college degree.

• In 2000, among young men living independently of their parents, 8% of those with a high school education were in poverty. Poverty peaked for this group at 17% around 2011 and has since declined to 12% in 2023.
• Among young men with some college education, poverty peaked at 12% around 2014, up from 4% in 2000. Poverty has fallen for this group since 2014 and stands at 8% as of 2023.
• Young men with a four-year college degree also experienced a slight uptick in poverty during the 2001 recession and Great Recession. In 2014, 6% of young college graduates were in poverty, up from 4% in 2000. Poverty among college graduates stands at 5% in 2023.

Labor force trends for young women are very different than for young men. There are occupational and educational differences between young women and men, and their earnings have followed different patterns.

Unlike the long-running decline for noncollege young men, young women without a college degree saw their labor force participation increase steadily from 1970 to about 1990.

By 2000, about three-quarters of young women with a high school diploma and 79% of those with some college education were in the labor force.

Labor force participation has also trended upward for college-educated young women and has consistently been higher than for those with less education.

After rising for decades, labor force participation for young women without a college degree fell during the 2001 recession and the Great Recession. Their labor force participation has increased slightly since 2014.

As of 2023, 69% of young women with a high school education were in the labor force, as were 78% of young women with some college education. Today’s level of labor force participation for young women without a college degree is slightly lower than the level seen around 2000.

The decline in labor force participation for noncollege women partly reflects the declining labor force participation for mothers with children under 18 years of age . Other research has suggested that without federal paid parental and family leave benefits for parents, some women with less education may leave the labor force after having a baby.

In contrast, labor force participation for young women with a college degree has fully recovered from the recessions of the early 2000s. Today, 87% of college-educated young women are in the labor force, the highest estimate on record.

Young women without a college degree have steadily increased their work hours over the decades. The past 10 years in particular have seen a significant increase in the share of employed noncollege women working full time, full year (with the exception of 2021).

• In 2023, 69% of employed young women with a high school education worked full time, full year, up from 56% in 2014. This share is the highest it’s ever been.
• In 2023, 65% of employed women with some college worked full time, full year, up from 58% in 2014. This is among the highest levels ever.

The trend in the share working full time, full year has been similar for young women with college degrees. By 2023, 78% of these women worked full time, full year, the highest share it’s ever been.

Unlike young men, young women without a college education did not see their earnings fall between 1970 and 2000.

The 2001 recession and Great Recession also did not significantly impact the earnings of noncollege young women. In the past 10 years, their median earnings have trended upward.

• For young women with a high school diploma, median earnings reached $36,000 in 2023, up from $30,900 in 2014.
• For those with some college, median earnings rose to $40,000 in 2023 from $37,700 in 2014.

For young women with a college degree, median earnings rose steadily from the mid-1980s until the early 2000s. By 2003, they reached $62,100, but this declined to $55,200 by 2014. In the past 10 years, the median earnings of college-educated young women have risen, reaching $65,000 in 2023.

In the mid-1980s, the typical young woman with a college degree earned about 48% more than her counterpart with a high school diploma. The pay gap among women has widened since then, and by 2014, the typical college graduate earned 79% more than the typical high school graduate. The gap has changed little over the past 10 years.

Noncollege young women living independently from their parents have experienced large household income gains over the past 10 years, measured at the median.

• In 2023, young women with a high school diploma had a median household income of $61,600, up from $48,100 in 2014.
• The pattern is similar for young women with some college education. Their median income rose to $75,200 in 2023 from $64,600 in 2014.

The median household income for young women with a four-year college degree is significantly higher than it is for their counterparts without a degree. College-educated young women have made substantial gains in the past 10 years.

The income gap between young women with and without a college degree has widened over the decades. In 1980, the median household income of young women with a college degree was 50% higher than that of high school-educated women. By 2014, the income gap had grown to 139%. Today, the household income advantage of college-educated women stands at 121% ($136,000 vs. $61,600).

Poverty trends for young women mirror those for young men, although young women are overall more likely to be in poverty than young men. The past 10 years have resulted in a steep reduction in the share of noncollege women in poverty.

• Today, 21% of young women with a high school diploma are living in poverty. This is down from 31% in 2014.
• 15% of young women with some college education live in poverty, compared with 21% in 2014.
• Young women with a college degree are consistently far less likely than either group to be living in poverty (5% in 2023).

Along with young adults’ rising incomes over the past 10 years, there’s been a substantial increase in their wealth. This part of our analysis does not look at men and women separately due to limitations in sample size.

In 2022, households headed by a young high school graduate had a median net worth of $30,700, up from $12,700 in 2013. Those headed by a young adult with some college education had a median net worth of $52,900, up from $15,700 in 2013.

The typical wealth level of households headed by a young college graduate was $120,200 in 2022, up from $46,600 in 2013.

There has not been any significant narrowing of the wealth gap between young high school graduate and young college graduate households since 2013.

Wealth increased for Americans across age groups over this period due to several factors. Many were able to save money during the pandemic lockdowns. In addition, home values increased, and the stock market surged.

• Most of the analysis in this chapter is based on the Annual Social and Economic Supplement collected by the U.S. Census Bureau. Information on net worth is based on a Federal Reserve survey, which interviews fewer households. Due to this smaller sample size, the net worth of households headed by a young adult cannot be broken out by gender and education. ↩
• Bureau of Labor Statistics data indicates that the labor force participation rate for men ages 25 to 54 has been declining since 1953. ↩
• This analysis looks at the earnings of employed adults working full time, full year. This measure of earnings is not uncommon. For example, the National Center for Education Statistics publishes a series on the annual earnings of 25- to 34-year-olds working full time, full year. ↩
• Other studies using hourly wages rather than annual earnings find that the college wage premium has narrowed. For example, researchers at the San Francisco Federal Reserve report that the college wage gap peaked in the mid-2010s but declined by just 4 percentage points to about 75% in 2022. ↩

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