how does research study help you in your daily life

How does research impact your everyday life?

“Research is to see what everybody else has seen, and to think what nobody else has thought.” – Albert Szent-Gyorgyi

What would the modern world look like without the bedrock of research?

First and foremost – without research, there’s no way you’d possibly be reading this right now, as the Internet was pioneered and developed (via a whole heap of exhaustive research…) by the European Organization for Nuclear Research , or CERN, the same association that produced the Large Hadron Collider.

Without research, we’d likely also be utterly defenceless to the brutal forces of nature. For example, without meteorology, we’d be unable to predict the path of violent storms, hurricanes and tornadoes, while a lack of volcanology research would leave a huge proportion of the world susceptible to the destruction of volcanic eruptions.

And it doesn’t end there.

Medical technology and discovery would be non-existent – no MRi , no anaesthetic, no birth control, no X-Ray machine, no insulin, no IVF, no penicillin, no germ theory, no DNA, and no smallpox vaccination – which, by the way would have wiped out one out of every nine babies had Jenner not researched and found a cure.

Source: University of Surrey

So not only is research an invaluable tool for building on crucial knowledge, it’s also the most reliable way we can begin to understand the complexities of various issues; to maintain our integrity as we disprove lies and uphold important truths; to serve as the seed for analysing convoluted sets of data; as well as to serve as ‘nourishment’, or exercise for the mind.

“…Aside from the pure pursuit of knowledge for its own sake, research is linked to problem solving,” John Armstrong, a respected global higher education and research professional, writes for The Conversation. “What this means is the solving of other people’s problems. That is, what other people experience as problems.

“It starts with a tenderness and ambition that is directed at the needs of others – as they recognise and acknowledge those needs,” he continues. “This is, in effect, entry into a market place. Much research, of course, is conducted in precisely this way beyond the walls of the academy.”

Ultimately, when we begin to look at research for what it truly is – a catalyst for solving complex issues – we begin to understand the impact it truly has on our everyday lives. The University of Surrey , set just a 10 minute walk from the centre of Guildford – ranked the 8 th best place to live in the UK in the Halifax Quality of Life Survey – is a prime example of a university producing high-impact research for the benefit of our global society.

Surrey’s experienced research team found that pollution levels inside cars were found to be up to 40 percent higher while sitting in queues, or at red lights, when compared to free-flowing traffic conditions. And with the World Health Organisation (WHO) placing outdoor air pollution among the top 10 health risks currently facing humans, linking to seven million premature deaths each year, Surrey took on the research challenge of finding an effective solution…

…And boy, did they get the results!

“Where possible and the weather conditional allowing, it is one of the best ways to limit your exposure by keeping windows shut, fans turned off and to try and increase the distance between you and the car in front while at traffic jams or stationary at traffic lights,” says Dr Prashant Kumar, Senior Author of the study. “If the fan or heater needs to be on, the best setting would be to have the air re-circulating within the car without drawing air from outdoors.”

Researchers actually found that closed windows or re-circulated air can reduce in-car pollutants by as much as 76 percent, highlighting how Surrey’s research outcomes could bring a wealth of invaluable global benefits.

As further testament to Surrey’s impactful research success, a study that uncovered high levels of Vitamin D inadequacy among UK adolescents has been published in the American Journal of Clinical Nutrition , and has now been used to inform crucial national guidance from Public Health England.

“The research has found that adolescence, the time when bone growth is most important in laying down the foundations for later life, is a time when Vitamin D levels are inadequate,” says Dr Taryn Smith, Lead Author of the study. The study forms part of a four-year, EU-funded project, ODIN, which aims to investigate safe and effective ways of boosting Vitamin D intake through food fortification and bio-fortification.

“The ODIN project is investigating ways of improving Vitamin D intake through diet,” continues Dr Smith, “and since it is difficult to obtain Vitamin D intakes of over 10ug/day from food sources alone, it is looking at ways of fortifying our food to improve the Vitamin D levels of the UK population as a whole.”

But the impact of Surrey’s research is broad and all-encompassing, with on-going projects into things like radiotherapy, dementia, blue light and human attentiveness, disaster monitoring, sustainable development, digital storytelling, and beyond. And benefits of research produced at the University of Surrey is not meant for the UK population alone; these are the issues that face us as an increasingly international and interconnected society, making research produced by world-class institutions like Surrey the tools to pave the way to bigger, brighter and healthier global future.

Find out more about studying for a postgraduate degree at Surrey by registering for one of Surrey’s Webinars .

Follow Surrey on Facebook , Twitter , Instagram , YouTube , Pinterest and LinkedIn

Feature image via Shutterstock

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10 Importance of Research in Our Daily Life

Table of Contents

In a world filled with information, it’s really important to understand the importance of research in our daily life . Whether you’re a professional in business, a scientist striving for breakthroughs, or a student navigating the academic landscape, research plays a crucial role in shaping your understanding and decisions. We need to conduct research to continually expand our knowledge base and stay informed in an ever-evolving world. In this article, we’ll discuss the reasons why research is important and its importance in our daily life.

Reasons Why Research is Important in Our Daily Life

The reasons why research is important in our daily lives are different and significant. From expanding knowledge to staying updated with the latest advancements, research provides the foundation for progress and knowledge that empowers us in various aspects of our everyday existence.

In addition, understanding how research plays an important role in our life is important, as it not only enhances our ability to gather information but also empowers us to make informed decisions. In jobs and work, research helps us think of new ideas, solve problems, and keep up with what’s happening in different areas.

It helps people learn more, ask questions, and develop a smart way of thinking. Also, doing research encourages us to be curious and keep learning all the time. It helps us see things from different angles and get better at adapting to a world that’s always changing. In the end, research is essential because it helps us improve ourselves and makes society better as a whole.

What is the Role of Research in Our Life?

Research plays an important role in our lives by helping us understand the world around us and make informed decisions. It is like detective work that scientists, scholars, and experts do to discover new things and find solutions to problems. In simple terms, research helps us answer questions and solve puzzles.

Imagine you have a question like, “How can we make our environment cleaner?” Researchers would study different aspects, like pollution, recycling, and renewable energy, to find the best solutions. This way, research helps us find ways to improve our lives and the world we live in.

Here are the following 10 importance of research in our daily life:

1. Expanding Knowledge Base

Research acts as a door to education and continuous learning. Regardless of your expertise, there is always more to discover about a subject. The process of research opens new paths for learning and personal growth, providing opportunities to build on existing knowledge.

2. Accessing the Latest Information

Staying informed is crucial, especially in dynamic fields. Research encourages the pursuit of the most recent information, preventing the risk of falling behind in rapidly evolving areas. This ensures that your insights are up-to-date and contribute to a comprehensive understanding of the subject matter.

3. Understanding the Competitive Landscape

In business and various other domains, understanding what you’re up against is vital. Researching competitors helps in formulating effective plans and strategies, identifying unique selling points, and staying ahead in the market. Beyond business, the research identifies challenges and adversaries, offering solutions and strategies for overcoming them.

4. Building Credibility

Credibility is the foundation of effective communication. Thorough research provides a solid base for ideas and opinions, making it difficult for others to question your knowledge. By relying on reputable sources, your credibility is enhanced, ensuring that your contributions are taken seriously.

5. Economic Development

Research plays a crucial role in driving economic growth. From market trends to consumer behavior, businesses rely on research to make strategic decisions that contribute to their success and, consequently, the economic development of a nation.

6. Exploring New Ideas

Research is the engine of innovation, driving the exploration of new ideas. It fuels creativity and pushes the boundaries of what is possible, leading to breakthroughs in various fields and shaping the world of tomorrow. Research is like a treasure hunt for smart solutions to problems, making life better for everyone. Without research, we might miss out on incredible inventions that could change the way we live!

7. Exploring New Ideas

Research introduces individuals to diverse perspectives and ideas. While individuals may enter the research process with preconceived notions, exposure to various viewpoints encourages openness to new ideas. This dynamic exploration may lead to shifts in opinions or the refinement of existing ones.

8. Facilitating Problem-Solving

Research is a valuable tool for problem-solving . Whether addressing personal or professional challenges, informed decisions are crucial. Through thorough research, individuals gain the necessary information to devise effective solutions, boosting confidence in decision-making.

9. Raising Awareness

The importance of research in raising awareness lies in its ability to provide valuable information and insights about various issues. Through systematic investigation and analysis, research helps uncover facts, trends, and challenges related to critical issues. This information serves as a foundation for creating awareness campaigns, educational initiatives, and advocacy efforts.

10. Cultivating Curiosity

Curiosity is the driving force behind continuous learning. Research nurtures curiosity by exposing individuals to different opinions, ideas, and possibilities. It rewards the innate human desire to explore, ensuring a perpetual state of intellectual growth.

In conclusion, the importance of research in our daily life is deep and complex. It’s not just about school or learning; it becomes a part of how we live every day. Research expands our knowledge base, keeping us in tune with the latest information and helping us understand the competitive landscape, be it in business or personal challenges. Furthermore, recognizing the reasons why research is important in our daily life empowers us to make informed decisions, solve problems effectively, and navigate the complexities of the modern world with confidence.

Moreover, it builds credibility, narrows the overwhelming scope of information, and enhances discernment. Research isn’t just about fixing problems; it helps us understand important things happening in society. It keeps us curious and always learning new stuff. Choosing to study isn’t just a choice; it’s a way to have a smarter, stronger, and more interesting life.

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Simple Answers to Scientific Questions

Importance Of Research In Daily Life

Whether we are students, professionals, or stay-at-home parents, we all need to do research on a daily basis.

The reason?

Research helps us make informed decisions.

It allows us to learn about new things, and it teaches us how to think critically.

There is an importance of research in daily life.

Let’s discuss the importance of research in our daily lives and how it can help us achieve our goals!

6 ways research plays an important role in our daily lives.

• It leads to new discoveries and innovations that improve our lives. Many of the technologies we rely on today are the result of research in fields like medicine, computer science, engineering, etc. Things like smartphones, wifi, GPS, and medical treatments were made possible by research.
• It informs policy making. Research provides data and evidence that allows policymakers to make more informed decisions on issues that impact society, whether it’s related to health, education, the economy, or other areas. Research gives insights into problems.
• It spreads knowledge and awareness. The research contributes new information and facts to various fields and disciplines. The sharing of research educates people on new topics, ideas, social issues, etc. It provides context for understanding the world.
• It drives progress and change. Research challenges existing notions, tests new theories and hypotheses, and pushes boundaries of what’s known. Pushing the frontiers of knowledge through research is key for advancement. Even when research invalidates ideas, it leads to progress.
• It develops critical thinking skills. The research process itself – asking questions, collecting data, analyzing results, drawing conclusions – builds logic, problem-solving, and cognitive skills that benefit individuals in their professional and personal lives.
• It fuels innovation and the economy. Research leads to the development of new products and services that create jobs and improve productivity in the marketplace. Private sector research drives economic growth.

So while not always visible, research underlies much of our technological, social, economic, and human progress. It’s a building block for society.

Conducting quality research and using it to maximum benefit is key.

Research is important in everyday life because it allows us to make informed decisions about the things that matter most to us.

Whether we’re researching a new car before making a purchase, studying for an important test, or looking into different treatment options for a health issue, research allows us to get the facts and make the best choices for ourselves and our families.

• In today’s world, there’s so much information available at our fingertips, and research is more accessible than ever.
• The internet has made it possible for anyone with an interest in doing research to access vast amounts of information in a short amount of time.

This is both a blessing and a curse; while it’s great that we have so much information available to us, it can be overwhelming to try to sort through everything and find the most reliable sources.

What is the importance of research in our daily life?

Research is essential to our daily lives.

• It helps us to make informed decisions about everything from the food we eat to the medicines we take.
• It also allows us to better understand the world around us and find solutions to problems.

In short, research is essential for our health, safety, and well-being. Without it, we would be living in a world of ignorance and misinformation.

What is the importance of research in our daily lives as a student?

As a student, research plays an important role in our daily life. It helps us to gain knowledge and understanding of the world around us.

• It also allows us to develop new skills and perspectives.
• In addition, research helps us to innovate and create new things. 
• Research is essential for students because it helps us to learn about the world around us. Without research, we would be limited to our own personal experiences and observations.
• Research allows us to go beyond our personal bubble and explore new ideas and concepts.
• It also gives us the opportunity to develop new skills and perspectives. 
• In addition, research is important because it helps us to innovate and create new things. When we conduct research , we are constantly learning new information that can be used to create something new.

This could be anything from a new product or service to a new way of doing things.

Research is essential for students because it allows us to be innovative and create new things that can make a difference in the world.

Consequently, while each person’s daily life routine might differ based on their unique circumstances, the role that research plays in our lives as students is an integral one nonetheless.

Different though our routines might be, the value of research in our lives shines through brightly regardless.  And that importance cannot be overstated .

How does research affect your daily life?

Every day, we benefit from the countless hours of research that have been conducted by scientists and scholars around the world.

• From the moment we wake up in the morning to the time we go to bed at night, we rely on research to improve our lives in a variety of ways.
• For instance, many of the items we use every day, such as our phones and laptops, are the result of years of research and development.
• And when we see a news story about a new medical breakthrough or a natural disaster, it is often the result of research that has been conducted over a long period of time.

In short, research affects our daily lives in countless ways, both big and small. Without it, we would be living in a very different world.

What are the purposes of research?

The word “research” is used in a variety of ways. In its broadest sense, research includes any gathering of data, information, and facts for the advancement of knowledge.

Whether you are looking for a new recipe or trying to find a cure for cancer, the process of research is the same.

You start with a question or an area of interest and then use different sources to find information that will help you answer that question or learn more about that topic.

“The purpose of research is to find answers to questions, solve problems, or develop new knowledge.”

It is an essential tool in business , education, science, and many other fields. By conducting research, we can learn about the world around us and make it a better place.

How to do effective research 

Research is a process of uncovering facts and information about a subject.

It is usually done when preparing for an assignment or project and can be either primary research, which involves collecting data yourself, or secondary research, which involves finding existing data.

Regardless of the type of research you do, there are some effective strategies that will help you get the most out of your efforts:

• First, start by clearly defining your topic and what you hope to learn. This will help you to focus your search and find relevant information more quickly.
• Once you know what you’re looking for, try using keyword searches to find websites, articles, and other resources that are relevant to your topic.
• When evaluating each source, be sure to consider its reliability and biases.
• Finally, take good notes as you read, and make sure to keep track of where each piece of information came from so that you can easily cite it later.

By following these steps, you can ensure that your research is both thorough and accurate.

How to use research to achieve your goals.

Achieving your goals requires careful planning and a lot of hard work.

But even the best-laid plans can sometimes go awry.

That’s where research comes in.

By taking the time to do your homework, you can increase your chances of success while also learning more about your topic of interest.

When it comes to goal-setting, research can help you to identify realistic targets and develop a roadmap for achieving them.

It can also provide valuable insights into potential obstacles and how to overcome them.

In short, research is an essential tool for anyone who wants to achieve their goals.

So if you’re serious about reaching your target, be sure to do your homework first.

So the next time you are faced with a decision, don’t forget to do your research!

It could very well be the most important thing you do all day.

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A Guide to Using the Scientific Method in Everyday Life

The  scientific method —the process used by scientists to understand the natural world—has the merit of investigating natural phenomena in a rigorous manner. Working from hypotheses, scientists draw conclusions based on empirical data. These data are validated on large-scale numbers and take into consideration the intrinsic variability of the real world. For people unfamiliar with its intrinsic jargon and formalities, science may seem esoteric. And this is a huge problem: science invites criticism because it is not easily understood. So why is it important, then, that every person understand how science is done?

Because the scientific method is, first of all, a matter of logical reasoning and only afterwards, a procedure to be applied in a laboratory.

Individuals without training in logical reasoning are more easily victims of distorted perspectives about themselves and the world. An example is represented by the so-called “ cognitive biases ”—systematic mistakes that individuals make when they try to think rationally, and which lead to erroneous or inaccurate conclusions. People can easily  overestimate the relevance  of their own behaviors and choices. They can  lack the ability to self-estimate the quality of their performances and thoughts . Unconsciously, they could even end up selecting only the arguments  that support their hypothesis or beliefs . This is why the scientific framework should be conceived not only as a mechanism for understanding the natural world, but also as a framework for engaging in logical reasoning and discussion.

A brief history of the scientific method

The scientific method has its roots in the sixteenth and seventeenth centuries. Philosophers Francis Bacon and René Descartes are often credited with formalizing the scientific method because they contrasted the idea that research should be guided by metaphysical pre-conceived concepts of the nature of reality—a position that, at the time,  was highly supported by their colleagues . In essence, Bacon thought that  inductive reasoning based on empirical observation was critical to the formulation of hypotheses  and the  generation of new understanding : general or universal principles describing how nature works are derived only from observations of recurring phenomena and data recorded from them. The inductive method was used, for example, by the scientist Rudolf Virchow to formulate the third principle of the notorious  cell theory , according to which every cell derives from a pre-existing one. The rationale behind this conclusion is that because all observations of cell behavior show that cells are only derived from other cells, this assertion must be always true. 

Inductive reasoning, however, is not immune to mistakes and limitations. Referring back to cell theory, there may be rare occasions in which a cell does not arise from a pre-existing one, even though we haven’t observed it yet—our observations on cell behavior, although numerous, can still benefit from additional observations to either refute or support the conclusion that all cells arise from pre-existing ones. And this is where limited observations can lead to erroneous conclusions reasoned inductively. In another example, if one never has seen a swan that is not white, they might conclude that all swans are white, even when we know that black swans do exist, however rare they may be.  

The universally accepted scientific method, as it is used in science laboratories today, is grounded in  hypothetico-deductive reasoning . Research progresses via iterative empirical testing of formulated, testable hypotheses (formulated through inductive reasoning). A testable hypothesis is one that can be rejected (falsified) by empirical observations, a concept known as the  principle of falsification . Initially, ideas and conjectures are formulated. Experiments are then performed to test them. If the body of evidence fails to reject the hypothesis, the hypothesis stands. It stands however until and unless another (even singular) empirical observation falsifies it. However, just as with inductive reasoning, hypothetico-deductive reasoning is not immune to pitfalls—assumptions built into hypotheses can be shown to be false, thereby nullifying previously unrejected hypotheses. The bottom line is that science does not work to prove anything about the natural world. Instead, it builds hypotheses that explain the natural world and then attempts to find the hole in the reasoning (i.e., it works to disprove things about the natural world).

How do scientists test hypotheses?

Controlled experiments

The word “experiment” can be misleading because it implies a lack of control over the process. Therefore, it is important to understand that science uses controlled experiments in order to test hypotheses and contribute new knowledge. So what exactly is a controlled experiment, then? 

Let us take a practical example. Our starting hypothesis is the following: we have a novel drug that we think inhibits the division of cells, meaning that it prevents one cell from dividing into two cells (recall the description of cell theory above). To test this hypothesis, we could treat some cells with the drug on a plate that contains nutrients and fuel required for their survival and division (a standard cell biology assay). If the drug works as expected, the cells should stop dividing. This type of drug might be useful, for example, in treating cancers because slowing or stopping the division of cells would result in the slowing or stopping of tumor growth.

Although this experiment is relatively easy to do, the mere process of doing science means that several experimental variables (like temperature of the cells or drug, dosage, and so on) could play a major role in the experiment. This could result in a failed experiment when the drug actually does work, or it could give the appearance that the drug is working when it is not. Given that these variables cannot be eliminated, scientists always run control experiments in parallel to the real ones, so that the effects of these other variables can be determined.  Control experiments  are designed so that all variables, with the exception of the one under investigation, are kept constant. In simple terms, the conditions must be identical between the control and the actual experiment.     

Coming back to our example, when a drug is administered it is not pure. Often, it is dissolved in a solvent like water or oil. Therefore, the perfect control to the actual experiment would be to administer pure solvent (without the added drug) at the same time and with the same tools, where all other experimental variables (like temperature, as mentioned above) are the same between the two (Figure 1). Any difference in effect on cell division in the actual experiment here can be attributed to an effect of the drug because the effects of the solvent were controlled.

In order to provide evidence of the quality of a single, specific experiment, it needs to be performed multiple times in the same experimental conditions. We call these multiple experiments “replicates” of the experiment (Figure 2). The more replicates of the same experiment, the more confident the scientist can be about the conclusions of that experiment under the given conditions. However, multiple replicates under the same experimental conditions  are of no help  when scientists aim at acquiring more empirical evidence to support their hypothesis. Instead, they need  independent experiments  (Figure 3), in their own lab and in other labs across the world, to validate their results. 

Often times, especially when a given experiment has been repeated and its outcome is not fully clear, it is better  to find alternative experimental assays  to test the hypothesis. 

Applying the scientific approach to everyday life

So, what can we take from the scientific approach to apply to our everyday lives?

A few weeks ago, I had an agitated conversation with a bunch of friends concerning the following question: What is the definition of intelligence?

Defining “intelligence” is not easy. At the beginning of the conversation, everybody had a different, “personal” conception of intelligence in mind, which – tacitly – implied that the conversation could have taken several different directions. We realized rather soon that someone thought that an intelligent person is whoever is able to adapt faster to new situations; someone else thought that an intelligent person is whoever is able to deal with other people and empathize with them. Personally, I thought that an intelligent person is whoever displays high cognitive skills, especially in abstract reasoning. 

The scientific method has the merit of providing a reference system, with precise protocols and rules to follow. Remember: experiments must be reproducible, which means that an independent scientists in a different laboratory, when provided with the same equipment and protocols, should get comparable results.  Fruitful conversations as well need precise language, a kind of reference vocabulary everybody should agree upon, in order to discuss about the same “content”. This is something we often forget, something that was somehow missing at the opening of the aforementioned conversation: even among friends, we should always agree on premises, and define them in a rigorous manner, so that they are the same for everybody. When speaking about “intelligence”, we must all make sure we understand meaning and context of the vocabulary adopted in the debate (Figure 4, point 1).  This is the first step of “controlling” a conversation.

There is another downside that a discussion well-grounded in a scientific framework would avoid. The mistake is not structuring the debate so that all its elements, except for the one under investigation, are kept constant (Figure 4, point 2). This is particularly true when people aim at making comparisons between groups to support their claim. For example, they may try to define what intelligence is by comparing the  achievements in life of different individuals: “Stephen Hawking is a brilliant example of intelligence because of his great contribution to the physics of black holes”. This statement does not help to define what intelligence is, simply because it compares Stephen Hawking, a famous and exceptional physicist, to any other person, who statistically speaking, knows nothing about physics. Hawking first went to the University of Oxford, then he moved to the University of Cambridge. He was in contact with the most influential physicists on Earth. Other people were not. All of this, of course, does not disprove Hawking’s intelligence; but from a logical and methodological point of view, given the multitude of variables included in this comparison, it cannot prove it. Thus, the sentence “Stephen Hawking is a brilliant example of intelligence because of his great contribution to the physics of black holes” is not a valid argument to describe what intelligence is. If we really intend to approximate a definition of intelligence, Steven Hawking should be compared to other physicists, even better if they were Hawking’s classmates at the time of college, and colleagues afterwards during years of academic research. 

In simple terms, as scientists do in the lab, while debating we should try to compare groups of elements that display identical, or highly similar, features. As previously mentioned, all variables – except for the one under investigation – must be kept constant.

This insightful piece  presents a detailed analysis of how and why science can help to develop critical thinking.

In a nutshell

Here is how to approach a daily conversation in a rigorous, scientific manner:

• First discuss about the reference vocabulary, then discuss about the content of the discussion.  Think about a researcher who is writing down an experimental protocol that will be used by thousands of other scientists in varying continents. If the protocol is rigorously written, all scientists using it should get comparable experimental outcomes. In science this means reproducible knowledge, in daily life this means fruitful conversations in which individuals are on the same page. 
• Adopt “controlled” arguments to support your claims.  When making comparisons between groups, visualize two blank scenarios. As you start to add details to both of them, you have two options. If your aim is to hide a specific detail, the better is to design the two scenarios in a completely different manner—it is to increase the variables. But if your intention is to help the observer to isolate a specific detail, the better is to design identical scenarios, with the exception of the intended detail—it is therefore to keep most of the variables constant. This is precisely how scientists ideate adequate experiments to isolate new pieces of knowledge, and how individuals should orchestrate their thoughts in order to test them and facilitate their comprehension to others.   

Not only the scientific method should offer individuals an elitist way to investigate reality, but also an accessible tool to properly reason and discuss about it.

Edited by Jason Organ, PhD, Indiana University School of Medicine.

Simone is a molecular biologist on the verge of obtaining a doctoral title at the University of Ulm, Germany. He is Vice-Director at Culturico (https://culturico.com/), where his writings span from Literature to Sociology, from Philosophy to Science. His writings recently appeared in Psychology Today, openDemocracy, Splice Today, Merion West, Uncommon Ground and The Society Pages. Follow Simone on Twitter: @simredaelli

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This has to be the best article I have ever read on Scientific Thinking. I am presently writing a treatise on how Scientific thinking can be adopted to entreat all situations.And how, a 4 year old child can be taught to adopt Scientific thinking, so that, the child can look at situations that bothers her and she could try to think about that situation by formulating the right questions. She may not have the tools to find right answers? But, forming questions by using right technique ? May just make her find a way to put her mind to rest even at that level. That is why, 4 year olds are often “eerily: (!)intelligent, I have iften been intimidated and plain embarrassed to see an intelligent and well spoken 4 year old deal with celibrity ! Of course, there are a lot of variables that have to be kept in mind in order to train children in such controlled thinking environment, as the screenplay of little Sheldon shows. Thanking the author with all my heart – #ershadspeak #wearescience #weareallscientists Ershad Khandker

Simone, thank you for this article. I have the idea that I want to apply what I learned in Biology to everyday life. You addressed this issue, and have given some basic steps in using the scientific method.

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In This Article Expand or collapse the "in this article" section Research Methods for Studying Daily Life

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Research Methods for Studying Daily Life by Carla Arredondo , Gloria Luong LAST REVIEWED: 24 April 2019 LAST MODIFIED: 24 April 2019 DOI: 10.1093/obo/9780199828340-0243

Methods for studying daily life have blossomed since the 1980s. Although these methods have been around for years, their popularity is always increasing as technological innovations have made the use of these methods easier and more reliable to employ. Methods for studying daily life typically include taking repeated real-time assessments of individual behaviors, physiology, and/or psychological experiences, over the course of an individual’s everyday life. These methods include experience sampling methodology (ESM), ecological momentary assessments (EMA), ambulatory assessments (AA), and daily diary or day reconstruction methods. All of these methods include repeated or detailed assessments of daily- life experiences but vary in terms of the frequency of assessments, technological tools to administer assessments, and timing of assessments (e.g., real time assessments versus retrospective recall). Given that these methods are intended to capture observations of psychological experiences in daily life, they require careful consideration of study design, measurements, and assessment tools. This article will provide a general overview of daily-life methods, including discussions about the different study designs and sampling methods. Furthermore, it will describe the advantages and limitations of using these methods along with examples of empirical studies that illustrate the usefulness of these techniques. It will also provide information on important considerations for sampling and measuring experiences in daily life and provide examples of the technology available for daily-life assessments.

Mehl and Conner 2012 is an all-encompassing review that discusses theoretical, methodological, and statistical considerations for conducting daily-life studies. Conner and Lehman 2012 focuses on providing practical advice for designing and conducting daily-life studies, while Stone and Shiffman 2002 outlines standardized reporting guidelines for researchers and provides recommendations for the information that should be included in study reports. Broderick, et al. 2003 and Green, et al. 2006 discuss issues of participant compliance and provide examples of how to monitor and improve participant compliance in daily-life studies. Barta, et al. 2012 discusses issues of measurement reactivity, whereby measurements bring about changes in study participants, and Conner and Reid 2012 is an example of testing for measurement reactivity. Lastly, Bolger, et al. 2003 provides an outline of areas of research that will need further investigation as intensive longitudinal designs become more prevalent.

Barta, W. D., H. Tennen, and M. D. Litt. 2012. Measurement reactivity in diary research. In Handbook of research methods for studying daily life . Edited by M. R. Mehl and T. S. Conner, 89–107. New York: Guildford Press.

Reviews factors that can affect measurement of constructs in daily-life studies. Discusses some of the sources of measurement reactivity, such as social desirability of the construct under investigation and conditions that influence reactivity of self-monitoring, such as participant motivation. They conclude with a review of studies demonstrating mixed findings on measurement reactivity and recommend that more daily-life studies explicitly test for measurement reactivity.

Bolger, N., A. Davis, and E. Rafaeli. 2003. Diary methods: Capturing life as it is lived. Annual Review of Psychology 54:579–616.

DOI: 10.1146/annurev.psych.54.101601.145030

Discusses areas of research that will need further consideration as intensive longitudinal study designs become more common. The article also discusses using technology to monitor objective measurements, such as heart rate, in conjunction with subjective experiences (i.e., mood). Also covered is the need to develop and test measures that can capture within-person changes and ideas for formulating research questions to further understand how these processes unfold in everyday life.

Broderick, J., J. Schwartz, S. Shiffman, M. Hufford, and A. Stone. 2003. Signaling does not adequately improve diary compliance. Annals of Behavioral Medicine 26:139–148.

DOI: 10.1207/S15324796ABM2602_06

Tested the extent to which signaling participants, via a programmed wristwatch, improved compliance in a twenty-four-day experience sampling study of individuals with chronic pain. The study used photo sensors to detect when diaries were opened and closed by participants to make an entry, and this information was cross-referenced with participant self-reports of compliance.

Conner, T. S., and B. Lehman. 2012. Getting started: Launching a study in daily life. In Handbook of research methods for studying daily life . Edited by M. R. Mehl and T. S. Conner, 89–107. New York: Guildford Press.

Provides an overview of important considerations for designing and conducting daily-life studies. It begins with preliminary considerations, such as participant characteristics, and moves into sampling strategies and platforms. Practical concerns, such as ethical considerations, are also discussed.

Conner, T. S., and K. A. Reid. 2012. Effects of intensive mobile happiness reporting in daily life. Social Psychology and Personality Science 3:315–323.

DOI: 10.1177/1948550611419677

An example of an experience sampling study that explicitly tested measurement reactivity. The study examined the extent to which there was measurement reactivity in a measure of happiness. Results demonstrate that overall the measure in question did not show reactivity. However, participant characteristics, such as depressive symptoms and trait neuroticism, contributed to measurement reactivity.

Green, A. S., E. Rafaeli, N. Bolger, P. E. Shrout, and H. T. Reis. 2006. Paper or plastic? Data equivalence in paper and electronic diaries. Psychological Methods 11:87–105.

DOI: 10.1037/1082-989X.11.1.87

See this article for a brief review of concerns regarding participant compliance in diary studies (pp. 87–88). The article also discusses other issues such as important considerations for improving the data quality from diary studies, recommendations for defining compliance, and individual differences in compliance (pp. 102–104). The article concludes with recommendations for improving diary studies.

Mehl, M. R., and T. S. Conner, eds. 2012. Handbook of research methods for studying daily life . New York: Guildford Press.

This book provides an all-encompassing review for researchers conducting daily-life studies. It is a resource for conducting high-quality research and provides guidelines to select and implement methods for studying daily life. The book begins with fundamental theoretical and methodological considerations for conducting these studies and then reviews statistical techniques that can be used to analyze these data. The book concludes with examples of these methods and techniques across different sub-fields in psychology.

Stone, A. A., and S. Shiffman. 2002 Capturing momentary, self-report data: A proposal for reporting guidelines. Guidelines for Momentary Research 24:236–243.

Proposes criteria for collecting momentary data. Argues that strategies for sampling daily-life data should be based on theoretical, statistical, and practical considerations of the phenomena in question that allow researchers to adequately collect data for hypothesis testing. The article also provides recommendations on reporting guidelines to facilitate study replication.

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What Is Research, and Why Do People Do It?

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• James Hiebert 6 ,
• Jinfa Cai 7 ,
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Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

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Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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11.1: The Purpose of Research Writing

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Learning Objectives

• Identify reasons to research writing projects.
• Outline the steps of the research writing process.

Why was the Great Wall of China built? What have scientists learned about the possibility of life on Mars? What roles did women play in the American Revolution? How does the human brain create, store, and retrieve memories? Who invented the game of football, and how has it changed over the years?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Whether you are a scientist, an artist, a paralegal, or a parent, you probably perform research in your everyday life. When your boss, your instructor, or a family member asks you a question that you do not know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process, and in this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer any question no matter how challenging.

Reasons for Research

When you perform research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you (and other people) have about the world. This is one of the most basic reasons for performing research.

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper. A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. And you may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Exercise \(\PageIndex{1}\)

Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

No matter what field of study you are interested in, you will most likely be asked to write a research paper during your academic career. For example, a student in an art history course might write a research paper about an artist’s work. Similarly, a student in a psychology course might write a research paper about current findings in childhood development.

Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires a lot of time, effort, and organization. However, writing a research paper can also be a great opportunity to explore a topic that is particularly interesting to you. The research process allows you to gain expertise on a topic of your choice, and the writing process helps you remember what you have learned and understand it on a deeper level.

Research Writing at Work

Knowing how to write a good research paper is a valuable skill that will serve you well throughout your career. Whether you are developing a new product, studying the best way to perform a procedure, or learning about challenges and opportunities in your field of employment, you will use research techniques to guide your exploration. You may even need to create a written report of your findings. And because effective communication is essential to any company, employers seek to hire people who can write clearly and professionally.

writing at work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

• Medical laboratory technician
• Small business owner
• Information technology professional
• Freelance magazine writer

A medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Exercise \(\PageIndex{2}\)

Think about the job of your dreams. How might you use research writing skills to perform that job? Create a list of ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job. How might these skills help you obtain that job?

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

• Choose a topic.
• Plan and schedule time to research and write.
• Conduct research.
• Organize research and ideas.
• Draft your paper.
• Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

As you may recall from Chapter 8 , to narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question—a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis. You may use your research question and your working thesis to create a research proposal. In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Before you start researching your topic, take time to plan your researching and writing schedule. Research projects can take days, weeks, or even months to complete. Creating a schedule is a good way to ensure that you do not end up being overwhelmed by all the work you have to do as the deadline approaches.

During this step of the process, it is also a good idea to plan the resources and organizational tools you will use to keep yourself on track throughout the project. Flowcharts, calendars, and checklists can all help you stick to your schedule. See Section 11.2 for an example of a research schedule.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources. Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper. You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported.

Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Now you are ready to combine your research findings with your critical analysis of the results in a rough draft. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis or purpose statement.

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism, or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

In the final step of the research writing process, you will revise and polish your paper. You might reorganize your paper’s structure or revise for unity and cohesion, ensuring that each element in your paper flows into the next logically and naturally. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting. When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written paper you can be proud of!

Exercise \(\PageIndex{3}\)

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

• In which steps of the research writing process are you allowed to change your thesis?
• In step 2, which types of information should you include in your project schedule?
• What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

• People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
• The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

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The Importance of Research to Students

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When exploring the impact of research, consider what it would be like if the automotive industry ceased all investigative efforts. The cars we drive would likely never improve in safety, comfort, or efficiency, and we would never know the benefits of the advancements we often take for granted. The same is true for the health sciences. Without research, advancements that have improved some lives and saved others may not have come to pass.

For universities, the research component allows for a broader educational experience whereby students are able to explore the effects of applying new thought processes through study and testing. Students are able to use that experience to see the practical application of their classroom experience represented in research projects. Cleveland University-Kansas City (CUKC), for example, offers a challenging curriculum, but also the opportunity to participate in various research studies on campus. ( Learn more about chiropractic here .)

Dr. Mark Pfefer, director of research at CUKC, collaborates with students on various projects. He said students have the opportunity to take an active role in research projects while at the same time learning about proper investigative techniques.

“We’ve had numerous students participate as co-authors on recent publications and presentations,” Pfefer said. “Students are taught strategies to search for information and assess the quality of the information found. Students learn good critical appraisal skills; all information is not the same, some information is good, and some is not.”

Research by Students in College

Pfefer said that students interested in research are mentored by faculty and assist in various ways, including literature searching, data collection, data entry, and manuscript development. The collective work between students and administrators has proven to be a successful combination, and he looks forward to the continuation of these efforts in future studies.

While time in the classroom is invaluable, having access to an on-site research department means that students are able to grow and challenge the boundaries that were established by their predecessors in the field. They are encouraged to open their minds and be open to the possibilities that research can reveal. Ultimately, they can become better health care professionals by engaging in work outside the classroom that challenges them in a similar fashion.

This will also have an impact on their future in their chosen profession by putting them in the position to attach their name to efforts that may have reshaped the parameters that were once the norm. Research can light the fire of curiosity that will continue throughout a professional career, and there is no end to what can be learned.

At Cleveland University-Kansas City (CUKC) , those are the exhilarating breakthroughs that research can deliver. It educates our students personally by opening their eyes to new possibilities. It rewards them professionally by getting their name out into the research community before they’ve even graduated.

Get to Know Cleveland University-Kansas City (CUKC )

CUKC is a private, nonprofit chiropractic and health sciences university in Overland Park, Kansas, a major suburb of the Kansas City metropolitan area. In addition to our 100-year legacy of offering the Doctor of Chiropractic (D.C.) degree, CUKC offers two-year degrees Radiologic Technology, and Biological Sciences. CUKC also offers the B.S. in Human Biology, B.S. in Exercise Science, the M.S. in Exercise Physiology and Sports Performance, and a 12-credit-hour Certificate in Sports Performance (CSP).

Explore our academic degrees/certifications here .

Research is a powerful part of the educational experience at CUKC and one we are proud to share with our students. As an example of the topics and issues explored, check out this research blog and our website for evidence-based research on chiropractic issues and topics .

CUKC is a student-focused, high academic quality University. Sound interesting to you? Get more information about CUKC here, and download a free guide to help you plot your college plan: Your Guide to Navigating College Financial Aid .

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Harvard Researchers Say These 5 Habits Could Help You Live a Longer, Healthier Life

New research from Harvard University found following these five habits could extend the years—and quality—of your life.

Lauren Wicks is a freelance writer and editor with a passion for food, wine, design and travel. Her work has also appeared on CookingLight.com, Veranda.com., Redbook.com, TravelandLeisure.com and FoodandWine.com, among other top lifestyle brands. Lauren currently lives in Birmingham, Alabama, with her husband, Price, and spends her free time haunting her favorite natural wine shop, reading cookbooks like novels, exploring the best food and wine destinations in the country, and hosting dinner parties for friends and neighbors. If she's not poring over a cookbook, she's likely working her way through a stack of historical fiction from the 19th and 20th centuries.

Lisa Valente is a registered dietitian and nutrition editor. She studied at the University of Vermont, where she completed her undergraduate studies in nutrition, food science and dietetics, and attended the dietetic internship program at Massachusetts General Hospital to become a registered dietitian. She went on to earn a master's degree in nutrition communication from the Friedman School of Nutrition Science and Policy at Tufts University. She was a nutrition editor at EatingWell for eight years. Prior to EatingWell, Lisa worked as a research dietitian at Griffin Hospital in Connecticut and also taught cooking and nutrition classes. She was a featured speaker at the Academy of Nutrition and Dietetics annual Food & Nutrition Conference & Expo (FNCE) in 2017.

By now, you probably already know that your diet and lifestyle can impact your risk for chronic diseases like cancer, heart disease, diabetes and more. But a brand-new study from Harvard University shows just how much of an impact our daily choices can have on our health and longevity.

This new study, published in BMJ , analyzed 34 years of data from over 110,000 adults who participated in the Nurses' Health and Health Professionals Follow-Up studies. The researchers found, on average, that the middle-aged participants who followed healthy lifestyle habits increased the number of years they lived without chronic disease, as well as their overall life expectancy.

"Previous studies have found that following a healthy lifestyle improves overall life expectancy and reduces risk of chronic diseases such as diabetes, cardiovascular disease and cancer, but few studies have looked at the effects of lifestyle factors on life expectancy free from such diseases," said lead author Yanping Li in a press release. "This study provides strong evidence that following a healthy lifestyle can substantially extend the years a person lives disease-free."

These lifestyle habits were: following a healthy diet, engaging in regular exercise, maintaining a healthy weight, drinking in moderation and not smoking. A healthy diet was defined by the Alternate Healthy Eating Index , which is similar to the Mediterranean Diet , placing an emphasis on whole, plant-based foods, fish, heart-healthy fats and whole grains, while limiting consumption of red meat, highly processed foods and sugar-sweetened beverages.

Regular exercise was defined as at least 30 minutes of moderate to vigorous activity each day, while a healthy weight was defined as a body mass index of 18.5-24.9. And moderate alcohol intake followed the current recommendation of up to one serving per day for women and up to two for men.

Women who followed four or five of these lifestyle behaviors experienced 10 more disease-free years, compared to those who didn't practice any on a regular basis. Men who exhibited four or five of these behaviors lived nearly seven years longer than those who didn't practice any on a regular basis. Men who were current heavy smokers and women who were in the obesity range for BMI were the most likely to have the shortest number of disease-free years.

"Given the high cost of chronic disease treatment, public policies to promote a healthy lifestyle by improving food and physical environments would help to reduce health care costs and improve quality of life," said senior author Frank Hu, chair of Harvard University's Department of Nutrition.

The Bottom Line

Overall, these habits are great lifestyle behaviors to start practicing now—no matter your age. However, while eating more veggies, exercising, watching your alcohol consumption and not smoking are all goals to strive for, science shows that the body mass index is outdated and there are many healthy people who live outside of this range.

"BMI isn't really a helpful measurement of how healthy someone is," says EatingWell's Senior Digital Nutrition Editor Lisa Valente, M.S., R.D. "It looks at one's height and weight but that's it, and that's not really enough data to say anything conclusively."

Valente says while BMI is an easy way for researchers to analyze a person, it's just a number and doesn't take into account that plenty of people in larger bodies have other amazing numbers, like cholesterol, blood pressure and blood glucose. She also noted that plenty of people with "healthy" BMIs may not be any healthier and could be engaging in unhealthy methods to maintain their weight.

Related Articles

Can daily coffee use increase your lifespan? Here's what the latest research says

You’ve probably heard of the many benefits of drinking coffee . There is no shortage of research studies attesting to the benefits of one (or two or three) cups of joe every day. Some of the studied benefits include reduction of risk of:

• Parkinson’s disease
• Type 2 diabetes
• Heart disease
• Prostate cancer
• Depression and suicide
• Cirrhosis of the liver
• Liver cancer

But did you know that coffee can also increase your lifespan? That’s what scientists behind a new research study announced recently.

So, what’s so special about coffee? How is it able to reduce our risk of dying from so many diseases? Let’s dive in.

Can coffee grounds be used to stop bleeding?  The answer might surprise you

More: Coffee with sugar can be good for your health and help you live longer, study suggests

What we know about coffee

Coffee is actually a complex mixture of over 1,000 different chemicals . It can pose a challenge for scientists to nail down which of these constituents provide the health benefits of coffee. In fact, coffee has had a checkered past. Some of its many chemicals have been identified as possible carcinogens – in 1991, the World Health Organization actually included coffee on a list of possible carcinogens. However, coffee was subsequently exonerated and removed from that infamous list.

Coffee is thought to be beneficial through the following mechanisms:

• Anti-inflammatory
• Reduced insulin resistance
• High amounts of antioxidants that can prevent or delay cell damage
• Lignans, which disrupt growth and spread of cancer cells
• Chlorogenic acid, which lowers blood sugar levels

What does the research show?

The newest study in the Annals of Internal Medicine analyzed coffee consumption habits of more than 170,000 people in the United Kingdom ages 37 to 73 and followed them for an average of seven years. Researchers found that those who drank between 1.5 to 3.5 cups of coffee per day were 16% to 21% less likely to die from all-cause, cancer-related and cardiovascular disease-related mortality during the study period than non-coffee drinkers.

But this is not the first study to look at the reduction in mortality from regular daily coffee use. A study published in 2015  in the journal Circulation tracked more than 200,000 participants for 30 years. Those who drank 3 to 5 cups of coffee a day were 15% less likely to die from all causes of mortality including cardiovascular disease, Parkinson’s disease and suicide. A more recent study in 2018 tracked over 500,000 participants across 10 years. Compared to non-coffee drinkers, participants who downed 6 to 7 cups daily had a 16% lower risk of early death.

In all studies, the benefit was enjoyed by those who drank both caffeinated and decaffeinated coffee – again, suggesting the benefit is from the myriad bioactive substances in coffee as opposed to caffeine.

Are you next?  More Americans than ever are being diagnosed with high blood pressure.

More: Which supplements are most likely to land you in the ER?

Association does not necessarily mean causation

The key takeaway from all these studies is that the data demonstrates an association between daily coffee consumption and a reduced risk of dying. But we should remember that a correlation between two things – in this case, coffee and decreased mortality – does not necessarily mean there’s direct causation. What we don’t really know is how much of the reduction in mortality is from the coffee itself, despite its known myriad benefits and this strong association.

There are many other so-called confounders that could influence this data. However, what I like about this new study is that researchers accounted for possible confounders by controlling for factors like smoking, presence of chronic medical problems, socioeconomic status and diet.

This new study is consistent with findings from a 2019 meta-analysis – which is one of the strongest evidence-based research studies that can be done. This meta-analysis examined 40 different studies that included 3.8 million participants. Researchers found that moderate coffee consumption (2 to 4 cups/day) was associated with reduced all-cause mortality compared to those who do not drink coffee. This benefit was observed irrespective of age, weight, alcohol or smoking use as well as the amount of caffeine present in the coffee.

But we must bear in mind that coffee-drinking study participants could have many other lifestyle factors contributing to reduced mortality such as a healthier diet or regular exercise routine. For example, researchers hypothesize that regular coffee drinkers will more likely opt for a cup of coffee versus a more sugar-heavy caffeine boost from an energy drink or soda.

The bottom line is that the new study is consistent with multiple studies showing a strong association between moderate daily coffee consumption (more than 1 cup/day) and a reduction in death from many causes. If you already drink coffee daily – caffeinated or decaffeinated – great! However, it’s no substitution for daily exercise and a healthy diet! If you get your caffeine from energy drinks or soda, consider switching to a cup of joe – but opt against adding a lot of sugar or whipped cream to your coffee or you might reduce the benefit.

TikTok’s ‘pomegranate pump’:  Does it actually work?

More: We've long been told salt is bad for you. Is it really?

Michael Daignault, MD, is a board-certified ER doctor in Los Angeles. He studied Global Health at Georgetown University and has a Medical Degree from Ben-Gurion University. He completed his residency training in emergency medicine at Lincoln Medical Center in the South Bronx. He is also a former United States Peace Corps Volunteer. Find him on Instagram  @dr.daignault

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Mobile phone ownership over time, who owns cellphones and smartphones, smartphone dependency over time, who is smartphone dependent, find out more, mobile fact sheet.

Large shares of Americans are connected to the world of digital information while “on the go” via smartphones and other mobile devices. Explore the patterns and trends that have shaped the mobile revolution below.

To better understand Americans’ smartphone and broadband adoption, Pew Research Center surveyed 5,733 U.S. adults from May 19 to Sept. 5, 2023. Ipsos conducted this National Public Opinion Reference Survey (NPORS) for the Center using address-based sampling and a multimode protocol that included both web and mail. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race and ethnicity, education and other categories.

Polls from 2000 to 2021 were conducted via phone. For more on this mode shift, please read our Q&A .

Here are the  questions used for this analysis , along with responses, and  its methodology ­­­.

The vast majority of Americans – 97% – now own a cellphone of some kind. Nine-in-ten own a smartphone, up from just 35% in Pew Research Center’s first survey of smartphone ownership conducted in 2011.

Substantial majorities of Americans across a wide range of demographic groups are cellphone owners. The same is true for smartphone ownership – though some differences do emerge, particularly by age, household income and level of formal education.

% of U.S. adults who say they own a __, by …

• RACE & ETHNICITY
• POLITICAL AFFILIATION

Today, 15% of U.S. adults are “smartphone-only” internet users – meaning they own a smartphone, but do not have home broadband service.

Source: Surveys of U.S. adults conducted 2013-2023. Data for each year is based on a pooled analysis of all surveys containing broadband and smartphone questions fielded during that year.

Reliance on smartphones for online access is especially common among Americans with lower household incomes and those with lower levels of formal education.

This fact sheet was compiled by Research Assistant  Olivia Sidoti , with help from Research Analyst  Risa Gelles-Watnick , Research Analyst  Michelle Faverio , Digital Producer  Sara Atske , Associate Information Graphics Designer Kaitlyn Radde and Temporary Researcher Eugenie Park .

Follow these links for more in-depth analysis of the impact of mobile technology on American life.

• Americans’ Social Media Use  Jan. 31, 2024
• Americans’ Use of Mobile Technology and Home Broadband  Jan. 31 2024
• Q&A: How and why we’re changing the way we study tech adoption  Jan. 31, 2024

Find more reports and blog posts related to  internet and technology .

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Research: More People Use Mental Health Benefits When They Hear That Colleagues Use Them Too

• Laura M. Giurge,
• Lauren C. Howe,
• Zsofia Belovai,
• Guusje Lindemann,
• Sharon O’Connor

A study of 2,400 Novartis employees around the world found that simply hearing about others’ struggles can normalize accessing support at work.

Novartis has trained more than 1,000 employees as Mental Health First Aiders to offer peer-to-peer support for their colleagues. While employees were eager for the training, uptake of the program remains low. To understand why, a team of researchers conducted a randomized controlled trial with 2,400 Novartis employees who worked in the UK, Ireland, India, and Malaysia. Employees were shown one of six framings that were designed to overcome two key barriers: privacy concerns and usage concerns. They found that employees who read a story about their colleague using the service were more likely to sign up to learn more about the program, and that emphasizing the anonymity of the program did not seem to have an impact. Their findings suggest that one way to encourage employees to make use of existing mental health resources is by creating a supportive culture that embraces sharing about mental health challenges at work.

“I almost scheduled an appointment about a dozen times. But no, in the end I never went. I just wasn’t sure if my problems were big enough to warrant help and I didn’t want to take up someone else’s time unnecessarily.”

• Laura M. Giurge is an assistant professor at the London School of Economics, and a faculty affiliate at London Business School. Her research focuses on time and boundaries in organizations, workplace well-being, and the future of work. She is also passionate about translating research to the broader public through interactive and creative keynote talks, workshops, and coaching. Follow her on LinkedIn  here .
• Lauren C. Howe is an assistant professor in management at the University of Zurich. As head of research at the Center for Leadership in the Future of Work , she focuses on how human aspects, such as mindsets, socioemotional skills, and leadership, play a role in the changing world of work.
• Zsofia Belovai is a behavioral science lead for the organizational performance research practice at MoreThanNow, focusing on exploring how employee welfare can drive KPIs.
• Guusje Lindemann is a senior behavioral scientist at MoreThanNow, in the social impact and organizational performance practices, working on making the workplace better for all.
• Sharon O’Connor is the global employee wellbeing lead at Novartis. She is a founding member of the Wellbeing Executives Council of The Conference Board, and a guest lecturer on the Workplace Wellness postgraduate certificate at Trinity College Dublin.

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Depression and Everyday Social Activity, Belonging, and Well-Being

Michael f. steger.

Colorado State University

Todd B. Kashdan

George Mason University

Dysfunctional social behavior has been implicated in the experience of depression. People with greater depressive symptoms report more frequent negative social interactions and react more strongly to them. It remains unknown, however, whether reaction strength differs depending on whether social interactions are positive or negative. Drawing on socio-evolutionary models of depression ( N. B. Allen & P. B. T. Badcock, 2003 ), we proposed that people with greater depressive symptoms should not only react more strongly to negative social interactions but also to positive social interactions and a sense of belonging. Using non-clinical samples, two daily process studies examined the role of depression in people's reactivity to social interactions in natural, ongoing, social contexts. In Study 1, the number of positive and negative social events showed a stronger relation to well-being among people with greater depressive symptoms. Study 2 extended this finding to perceptions of belonging in memorable social interactions, finding a stronger link between belonging and well-being among people with greater depressive symptoms. Together these studies provide the first indication that depressive symptoms may sensitize people to everyday experiences of both social rejection and social acceptance.

A lonely man is a lonesome thing, a stone, a bone, a stick, a receptacle for Gilbey's gin, a stooped figure sitting at the edge of a hotel bed, heaving copious sighs like the autumn wind. ( Cheever, 1991 )

Humans have a profound need to connect with others and gain acceptance into social groups (i.e., belonging; Baumeister & Leary, 1995; Deci & Ryan, 2000 ). People form bonds readily and organize much of their behavior around establishing and maintaining those bonds. Further, people suffer when relationships deteriorate and social bonds are severed. Although feeling disconnected from others and experiencing a lack of belonging bothers everyone, depressed people may be particularly sensitive to these painful social encounters ( Allen & Badcock, 2003 ). Because of the importance of social experiences to people's well-being (e.g., Diener & Seligman, 2000 ), and to the etiology and maintenance of depression (e.g., Allen & Badcock, 2003 ; Barnett & Gotlib, 1988 ; Coyne, 1976b ), it is vital to examine how depressed people's well-being is enhanced or eroded by positive and negative social interactions. The present research used two daily process studies to test the degree to which naturally occurring positive and negative social interactions interact with depressive symptoms to predict well-being.

Depression and Social Dysfunction

The motivational and affective profile associated with depression can be expected to influence the ability to feel a sense of social belonging and how, in turn, these feelings influence well-being. It is rare for a social interaction to provide objective evidence of rejection or acceptance, leaving the ultimate impact of social interactions up to people's perceptions. When people experience positive social interactions they should be more likely to feel a sense of belonging. However, depressed people's social information-processing biases appear to make it less likely that they will perceive cues of acceptance and belonging in social interactions. For example, in laboratory studies, clinically depressed people show preferential attention to sad faces, adjectives, and emotion words (e.g., Gotlib, Kasch, et al., 2004 ; Gotlib, Krasnoperova, Yue, & Joormann, 2004 ; Mogg & Bradley, 2005 ). Further, depressed people typically view ambiguous social interactions as negative, attribute these negative outcomes to the self, and act in accord with expectations that negative social interactions are likely and costly ( Beck, Rush, Shaw, & Emery, 1979 ; Joiner & Coyne, 1999 ). It appears that depressed people should be more likely to pay attention to negative social interactions, and less likely to feel a sense of belonging.

Evidence does, indeed, suggest that depressed people often fail in their quest to satisfy their need for belonging in relationships (e.g., Hagerty, Williams, Coyne, & Early, 1996 ), with potentially severe consequences ( Leary, 1990 ). Depressed people report fewer intimate relationships, and elicit fewer positive, caring responses and more negative, rejecting responses from others ( Gotlib, 1992 ; Joiner & Coyne, 1999 ; Segrin & Abramson, 1994 ). Depressed people also appear to induce negative affect in others, which, in turn, elicits rejection and the loss of socially rewarding opportunities ( Coyne, 1976a ; Joiner & Katz, 1999 ).

Dulled or Heightened Reactions to Negative and Positive Stimuli?

A synthesis of the existing literature leads us to conclude that people with greater depressive symptoms are more likely to create difficult social situations, have worse interactions, and preferentially direct their attention to negative emotional social stimuli. As a result of this cascade of social dysfunction, it seems possible that more depressed people are sensitized to negative social interactions. A number of studies have examined sensitivity to rewards and punishments among clinically depressed samples. Generally, laboratory studies show that clinically depressed people experience dulled, not heightened, reactions to negative, punishment cues and positive, reward cues (e.g., winning/losing small to large amounts of money in mock gambling paradigms; Henriques & Davidson, 1990 , 2000 ; Sloan, Strauss, & Wisner, 2001 ). This dulled reactivity has also been extended to social stimuli (e.g., sad and amusing films; Rottenberg, Kasch, Gross, & Gotlib, 2002 ). Researchers have concluded from such results that dulling of reactions to positive and negative stimuli is a hallmark of major depressive disorder ( Henriques & Davidson, 1991 ; Rottenberg, 2005 ). Nonetheless, there are some indications that clinically depressed people show greater reactivity to positive reward cues ( Must et al., 2006 ), particularly if they attribute the onset of positive events in everyday life to global and stable causes ( Needles & Abramson, 1990 ).

However, social experience is best understood as a dynamic, communication-driven process with progressive reciprocal influences of actors, partners, and situational demands (e.g., Gable & Reis, 1999 ; Gilbert, 2006 ). Cross-sectional survey methods miss this dynamic interchange, asking research participants to retrospectively evaluate and generalize across varying experiences in different social contexts. Laboratory studies often employ singular, sometimes arbitrary, de-contextualized stimuli (e.g., words or pictures of facial expressions; Gotlib, Kasch, et al., 2004 ). For example, it is not clear that images of an angry person would hold the same implications for social acceptance and rejection as a real-world disagreement with a friend. Daily process studies are able to capture people's everyday social experiences, and their reactions to them, as they unfold in their typical environments. This method confers ecological validity that is often sacrificed with other approaches and can shed light on how people with depressive symptoms react to life events. For example, this type of research has shown that people with greater depressive symptoms reported less intimacy, enjoyment, and perceived influence in everyday social interactions (e.g., Nezlek, Hampton, & Shean, 2000 ; Nezlek, Imbrie, & Shean, 1994 ) and report less day-to-day stability in well-being (Gable & Nezlek, 1998). Of particular relevance to this study, researchers have found that depressed people were more reactive to positive life events, reacting to both positive and negative events with more strongly enhanced positive affect, among other indicators of well-being ( Nezlek & Gable, 2001 ). Whereas prior laboratory studies indicated dampened reactivity to positive, reward cues among more depressed people (e.g., Sloan et al., 2001 ), when positive events occur outside of the laboratory, an opposite effect is found (see Needles & Abramson, 1990 for a 6-week prospective investigation). Providing additional weight to the notion that results from laboratory studies diverge from studies with stronger links to everyday functioning, a recent longitudinal epidemiological study showed that depressed people benefit more from becoming married compared to less depressed people ( Frech & Williams, 2007 ).

There is another reason why Nezlek and Gable (2001) may have found greater reactivity to life events in contrast to laboratory studies. Lab-based studies have focused on people with clinical levels of depression, often carrying the diagnosis of Major Depressive Disorder, whereas Nezlek and Gable modeled depressive symptoms on a continuum. Clinical levels of depression may represent a significantly more debilitating condition (e.g., Allen & Badcock, 2003 ), leading clinically depressed people to feel numb and less reactive to negative social experiences as a self-protective strategy (e.g., Rottenberg, 2005 ). On the other hand, evidence is emerging that depressive symptoms lie on a continuum of increasing impairment (e.g., Backenstrass et al., 2006 ; Priciandaro, & Roberts, 2005 ; Ruscio & Ruscio, 2002 ). Subthreshold depression may be a pre-morbid manifestation of psychopathology, and, in fact, people with subthreshold depression are at substantial risk of developing major depressive disorder (e.g., Cuijpers, Smit, van Straten, 2007 ; Fogel, Eaton, & Ford, 2006 ; Regeer et al., 2006 ; Sherbourne et al., 1994 ) as well as other adverse outcomes such as suicidal behavior ( Fergusson, Horwood, Ridder, & Beautrais, 2005 ). Understanding how social experiences influence the well-being of people with subthreshold depression may shed light on the progression to disorder. One study has examined the reactivity of clinically depressed people to life events in their naturalistic environments. This study split the difference, so to speak, converging with laboratory studies of clinically depressed people in finding dulled reactivity to negative life events, and converging with daily process studies of subthreshold samples in finding heightened reactivity to positive life events ( Peeters, Nicolson, Berkhof, Delespaul, & DeVries, 2003 ).

The social risk hypothesis of depression ( Allen & Badcock, 2003 ) provides one account of how subthreshold levels of depressive symptoms could have evolved to help people reduce the risk of being excluded from social groups. Ancestral humans faced survival challenges that were best met through participation with reliable others in social groups. Being accepted by a social group increased the likelihood of survival, whereas being rejected decreased the likelihood of survival as well as the ability to find suitable mates to produce offspring and continue one's genetic lineage. Allen and Badcock argued that people with subclinical levels of depressive symptoms should be highly reactive to cues indicative of threats to one's social resources. The central goal of behavior, then, is to ensure that the benefits that a person provides to a social group far outweigh any perceived burden; a positive value-to-burden ratio is synonymous with secure group status. As people perceive their social value falling and their subsequent risk of social exclusion rising, depressive symptoms direct attentional resources to ongoing social information. With this social attunement, behavior can be modified as needed to prevent social rejection or exclusion. Likewise, people's behavioral repertoire will be subdued to prevent further conflict and potentially catastrophic loss (e.g., rejection from the group or physical harm); such responses would be marked by submissiveness, and inhibition of exploratory and resource-seeking behaviors ( Gilbert, 1992 ; 2006 ). These responses mimic depressive symptoms, and research has shown that people with greater depressive symptoms react to perceived dominance from others with exacerbated submissiveness and feelings of inferiority compared to people with lesser depressive symptoms (e.g., Zuroff, Fournier, & Moskowitz, 2007). Clinical levels of depression may represent a malfunctioning of the evolved mental apparatus that is proposed to monitor risk for social exclusion. Instead of being sensitive to possible rejection, clinical depression might reflect a lack of context sensitivity such that any situation that is not objectively positive is viewed as threatening. As a result, submissive, self-deprecating psychological and behavioral reactions are rigidly enacted ( Allen, Gilbert, Semedar, 2004 ).

This model prioritizes social events over other types of life events, making Nezlek and Gable's (2001) study an imperfect test. A better test of this model is provided by a daily process study showing that people with greater depressive symptoms react more strongly (i.e., experience more distress) in response to social stressors than do people with lesser depressive symptoms (e.g., O'Neill, Cohen, Tolpin, & Gunthert, 2004 ). Thus, there is some evidence for the central proposition of the social risk hypothesis in the naturally occurring social experiences of people with subthrehold depressive symptoms.

Theories such as the social risk hypothesis are fairly explicit in predicting that people with greater depressive symptoms should react more strongly to threats of social exclusion, as would be indicated by negative social interactions or social stressors ( Allen et al., 2004 ; Gilbert, 2006 ). This perspective is in line with the prevailing tradition in psychology to focus on negative expressions of human behavior and psychopathology rather than on the full spectrum of human behavior, including positive experiences and well-being ( Seligman & Czikszentmihalyi, 2000 ). Therefore, as currently articulated, socio-evolutionary theories neither predict nor account for evidence of stronger reactions to positive events among people with subthreshold ( Nezlek & Gable, 2001 ) and clinical depression ( Peeters et al., 2003 ). We believe that these models can be extended to predict heightened reactions to positive social interactions among people with subthreshold depressive symptoms.

A Balanced Model of Depressive Symptoms as Social Sensitizer

The social risk hypothesis frames social relationships in terms of social value and social burdens – if social burden exceeds, or even equals, one's social value, then one is at elevated risk of being excluded and attracting negative attention (e.g., Allen et al., 2004 ). Humans presumably evolved the ability to appraise how they are being viewed by others (e.g., if they are attracting negative attention from their group, Gilbert, 1997 ). According to this perspective, depressive symptoms evolved to facilitate appraisals of falling social value and rising social burden, and it is because of this function that they sensitize people to threats of social rejection. It seems equally likely that depressive symptoms help people identify when their social value is rising and their social burden is falling; positive social interactions signal rising social value, and therefore more secure belonging. Thus, people with greater depressive symptoms can be expected to capitalize on positive social interactions by experiencing enhanced well-being. From the perspective of a social group, depressed people are prone to unsatisfying, problematic relationships and are often avoided as interaction partners (e.g., Joiner & Katz, 1999 ). Happy people, in contrast, tend to possess good relationships, and people with higher positive affect are evaluated more favorably by interaction partners (e.g., Gable, Reis, Impett, & Asher, 2004 ; Lyubomirsky, King, & Diener, 2005 ). Thus, it would be adaptive for people with greater depressive symptoms to be highly reactive to positive social interactions because their increased well-being would make them more attractive as social partners (decreasing the likelihood of future rejection and solidifying their social membership). In short, there is no particular reason from a socio-evolutionary standpoint to postulate that depressive symptoms might have evolved only to sensitize people to risks of disadvantageous social value/burden ratios. We argue that people with subthreshold depression may be uniquely attentive to both positive and negative social cues – and may be expected to be particularly reactive to their social experiences – because such cues provide valuable information about their degree of acceptance and security within their social group. In our model, mild to moderate depressive symptoms direct people's attention to seeking and establishing, not just protecting, belonging.

The Present Investigation

Social experiences are strongly implicated in the etiology and maintenance of depression. We propose that mild to moderate levels of depressive symptoms sensitize people to cues regarding their degree of social belonging, extending previous theories to include indicators of rising belonging. That is, when people with greater depressive symptoms perceive their belonging to be at risk, as indicated by negative social interactions, they should react more strongly with decreases in well-being. Similarly, when they perceive their belonging to be secure, as indicated by positive social interactions, they should react more strongly with increases in well-being. We are aware of no previous research that has examined the reactivity of people with mild to moderate depression symptoms to the full spectrum of positive and negative social interactions.

Inquiry into the ramifications of social experiences can advance by examining how people differing in depressive symptoms act and react in their natural, ongoing social environments. Therefore, we conducted two daily process studies. In Study 1, we examined how depressive symptoms influenced reactivity to an objective list of specific negative and positive social interactions. To better understand reactions to these social events, we assessed affective (positive and negative affect) and cognitive (appraisals of how meaningful and satisfying life is) markers of well-being. Because no finite list can hope to capture all of the significant interactions people might experience, in Study 2, we examined the role of depressive symptoms in response to appraisals of memorable social interactions. Thus, using both objective and subjective measures of interaction quality, we tested our proposal that depressive symptoms attune people to signals of social rejection as well as belonging. Drawing on previous theory and research, we hypothesized people with greater depressive symptoms would report (1) more frequent negative, and less frequent positive, social interactions, and (2) greater reactivity in terms of affective and cognitive markers of well-being to positive social interactions, negative social interactions, and perceptions of belonging.

Study 1 focused on relations between positive and negative social interactions and well-being among people with varying depressive symptoms. Previous lab-based research examined depressive symptoms in the context of positive and negative social stimuli, such as photos of facial expressions, in clinically depressed samples (e.g., Gotlib, Kasch, et al., 2004 ), and some daily process research examined links between subthreshold depressive symptoms and naturalistic daily life events (e.g., Nezlek & Gable, 2001 ). However, despite the strong role social functioning is thought to play in the etiology and exacerbation of depressive symptoms (e.g., Coyne, 1976a ), research is lacking on the reactivity of people with mild to moderate depressive symptoms to both positive and negative social events. To understand how people with greater depressive symptoms react to positive and negative social interactions, we assessed relations between social interactions and a broad range of well-being measures. Specifically, we measured cognitive evaluations of life satisfaction and meaning in life as well as positive and negative affect. Thus, we assessed what we refer to as cognitive well-being (CWB) and affective well-being (AWB). We used a 21-day daily process method in which participants recorded the occurrence of a variety of social interactions and their well-being each day. This method generates hierarchically structured data in which daily life ratings are nested within individuals. Direct relations between well-being and social experiences reported in daily life were assessed. Additionally, cross-level interactions assessed the extent to which relations between day-to-day social interactions and well-being varied across levels of depression. Thus, we looked at how many positive and negative social interactions people with greater depressive symptoms reported. In addition, we examined whether people with greater depressive symptoms reacted to positive and negative social interactions more strongly in terms of AWB and CWB.

Participants

Participants were recruited from undergraduate psychology courses at a large Midwestern university ( N = 106; M age = 19.7, SD = 3.1; 66% female; 74% European-American), and completed the depression measure and daily reports in exchange for course credit. Missing responses and invalid response patterns (i.e., no day-to-day variation in responses, same rating score given for all items) resulted in a final sample size of 104.

Global Depression

Depressive symptoms were assessed using the Center for Epidemiological Studies-Depression scale (CES-D; Radloff, 1977 ). Twenty items were rated from 0 ( Rarely or None of the Time ) to 3 ( Most or All of the Time ) (α = .86). 1 The mean symptom severity of this sample ( M = 16.7, SD = 10.5) was roughly 0.5 SD lower than clinical sample means ( Radloff, 1977 ), with 38.5% of the sample scoring above the mild to severe depression cutoff score (17) suggested for comparisons between normal and clinical populations ( Radloff, 1977 ). Thus, this sample appears to have sufficient individuals reporting subthreshold symptoms to be considered at risk for significant distress and/or impairment.

Daily Social Interactions

Positive and negative social interactions were assessed using five positive (e.g., “Flirted with someone or arranged a date,” “Went out socializing with friends/date (e.g., party, dance clubs”) and five negative items (e.g., “A disagreement with a close friend or steady date was left unresolved,” “Was excluded or left out by my group of friends”) from the Daily Events Survey ( Butler, Hokanson, & Flynn, 1994 ). Items were rated on whether they happened (1) or not (0). Principal axis factor analysis with Promax rotation revealed that items assorted into three factors. One factor ( eigenvalue = 1.85) was comprised of three positive social items concerning friends and flirting; the second factor ( eigenvalue = 1.55) was comprised of all five negative social interaction items; the third factor ( eigenvalue = 1.05) was comprised of the two items concerning interactions with steady romantic partners. Because the negative social interactions formed a clear factor and the two small positive factors were highly related ( factor correlation = .55), the items were assorted into one negative social interaction scale and one positive social interaction scale. Reliability estimates were obtained from Hierarchical Linear Modeling 6.0 (HLM; Raudenbush, Bryk, Cheong, & Congdon, 2004), supporting the consistency of the two scales ( reliability = .93 and .91, for positive and negative social interactions, respectively).

Daily Cognitive Well-Being

Cognitive well-being was assessed by summing three items used in previous research ( Steger, Kashdan, & Oishi, 2008 ) assessing meaning in life (i.e., “How meaningful does your life feel?” “How much do you feel your life had purpose today?”) and life satisfaction (“How satisfied are you with your life?”) rated from 1 ( Not at All ) to 7 ( Absolutely ). Meaning and life satisfaction items were highly interrelated (γ = 1.14, SE = .03, t (96) = 35.20, p < .000)1( reliability = .98).

Daily Affective Well-Being

Affective well-being was assessed by subtracting average daily negative affect ratings (i.e., sluggish, afraid, sad, anxious, and angry) from average daily positive affect ratings (i.e., relaxed, proud, excited, appreciative, enthusiastic, happy, satisfied, curious, and grateful) (see Schimmack & Diener, 1997 ). Affective items were rated from 1 ( Very Little/Not at All ) to 5 ( Extremely ). These emotional adjectives are used frequently in experience-sampling studies of emotion (e.g., Kashdan & Steger, 2006 ). PA and NA subscale scores were highly interrelated (γ = −.11, SE = .00, t (102) = 25.062 p < .0001) ( reliability = .93).

During an initial orientation session, participants answered demographic questions, and received a packet of 21 duplicate daily reports containing the daily measures specified above, along with instructions to complete a single form at the end of each day or within one hour after waking. Participants were told in class during recruitment and in subsequent emails that it was extremely important to only complete reports at the end of each day, and not to complete more than one report on any single day. After 3 weeks, participants turned in their daily reports. All participants completed the CES-D three weeks into the study, on the day when they turned in their daily reports. Participants received course credit for their completed daily reports and survey responses.

The data consisted of 2,118 daily reports nested within 104 people. Participants reported mean daily CWB of 14.3 ( SD = 3.9), which is above the midpoint of 12, and mean daily AWB of 0.8 ( SD = 1.3). This positive number means that participants reported more positive emotions than negative emotions per day. Participants reported more positive social interactions ( M = 1.11, SD = 1.19) than negative social interactions ( M = 0.33, SD = 0.69). Using recommended formulas for calculating intraclass correlations within multilevel datasets, we calculated the proportion of variance in daily scores due to between-person factors (individual differences) compared to within-person factors (days) ( Raudenbush & Bryk, 2002, p. 36, 71 ). In each case, the percentage refers to the proportion of variance attributable to between-person factors ( Table 1 ). From these proportions, we can see that only about one-third to two-fifths of the variance in daily positive and negative social interactions, and AWB, are due to stable, dispositional factors, with the majority of the variance attributable to fluctuating daily factors. The reverse case was true for CWB, which appears more stable overall.

Descriptive statistics for Studies 1 and 2.

Notes . The following terms were derived from “empty” models, as described in Equations 1 and 2 (except with the depression term excluded from Equation 2 ), r ij = within-persons variance; u 0j = between-persons variance; ICC = proportion of variance in each variable attributable to stable individual differences. Separate models were conducted for each variable.

Coefficients representing daily social interactions and well-being were estimated for each person (Level-1) and individual differences in these variables accounted for by depressive symptoms were estimated (Level-2). Level-1 variables were person-centered and Level-2 depression ratings were standardized and entered uncentered. First, we first tested whether more depressed people reported fewer positive and more negative social interactions than less depressed people using open HLM equations with CES-D scores as a Level 2 covariate of the intercept of positive and negative social interactions.

where Y ij is either positive or negative social interactions reports for person j on day i, β 0j is a random coefficient representing the intercept, or average daily number of interactions for person j, and r ij represents error. At Level 2, β 0j is predicted by γ 00 , which is the average of Level 1 coefficients describing daily reports of interactions, γ 01 , which is each participants' standardized CES-D scores score, and u 0j , which is error.

People with more depressive symptoms reported marginally fewer positive social interactions (γ = −.02, SE = .01, t (102) = 1.79, p < .10), and significantly more negative social interactions (γ = .03, SE = .01, t (102) = 4.23, p < .0001).

We next tested whether people with greater depressive symptoms were more reactive to positive and negative social interactions using an equation in which well-being was predicted by an intercept and number of positive and negative social interactions, with CES-D scores as a Level 2 covariate of each term.

where Y ij is either CWB or AWB scores for person j on day i, β 0j is a random coefficient representing the intercept, or average daily number of interactions for person j, β 1j represents each participants' daily positive social interactions, β 2j represents each participants' daily negative social interactions, and r ij represents error. At Level 2, β 0j is predicted by γ 01 , which is the average of Level 1 coefficients describing the relations between both positive and negative social interactions and the corresponding Y ij (either CWB or AWB), γ 00 , which is each participant's standardized CES-D score, and u 0j , which is error. Thus, γ 01 reflects the influence of participants' depressive symptoms on their average daily CWB or AWB. β 1j is predicted from γ 10 , which reflects the Level 1 coefficients describing the average relation between positive social interactions and CWB or AWB, γ 11 , which represents the influence of depressive symptoms on daily CWB and AWB, and u 1j , which is error. β 2j is modeled identically, but using reports of negative social interactions rather than positive social interactions. Thus, we modeled daily CWB and AWB as a function of within-person reactivity (slopes) to positive and negative social interactions, γ 10 and γ 20 , allowing these relations to differ for different participants, and using depression scores to predict these individual differences in reactivity, γ 11 and γ 21 .

Across participants, positive, γ 10 , and negative, γ 20 , social interactions were significantly related to well-being ( Table 1 ). People with greater depressive symptoms reported lower average daily CWB and AWB, γ 01 . Depression also moderated relations between daily positive, γ 11 , and negative, γ 21 , social interactions and daily CWB, and between daily positive social interactions, γ 21 , and daily AWB. To decompose the interaction between depression and social interactions we calculated means at +1 SD and −1 SD. Compared to people with lesser depressive symptoms, people with greater depressive symptoms reported larger positive relations between daily positive social interactions and CWB (see Figure 1 ) and AWB, and larger negative relations between daily negative social interactions and CWB. 2 Positive and negative social interactions, along with the moderating effect of depressive symptoms accounted for 27% of the variance in daily cognitive well-being and 42% of the variance in daily affective well-being (see Table 2 ).

Depressive symptom severity moderates relations between positive social interactions; and daily cognitive well-being (Study 1)

Depression, social interactions, and well-being, Study 1.

As predicted from previous research and theory, people with greater depressive symptoms reported somewhat fewer positive social interactions and significantly more negative social interactions. Other results extended previous research and provided the first support for our expansion of socio-evolutionary models of depression to predict greater sensitivity to both negative and positive social interactions. Specifically, people with greater depressive symptoms were more reactive to both positive and negative daily social interactions. Thus, although previous research has indicated that people with greater depressive symptoms react more strongly to positive life events (e.g., Nezlek & Gable, 2001 ; Peeters et al., 2003 ), the present research is the first to develop a conceptual rationale for, and support with data, greater reactivity to social interactions, specifically.

Study 1 found that people with greater depressive symptoms reacted more strongly to social interactions included on a short list of positive and negative interactions. A priori lists of interactions might not be an accurate representation, in terms of number and type, of people's interactions in a given day. People undoubtedly engaged in social interactions that were not included on the list. Further, people likely differ in their interpretations of the magnitude of events and in how upsetting the negative events were, or how uplifting the positive events were. For example, some people may not worry about leaving a minor disagreement with a friend unresolved. On the other hand, an unresolved major disagreement may cause some participants to ruminate heavily.

To obtain more naturalistic and representative samples of people's daily social lives, we conducted a second study, allowing participants to rate self-selected “memorable” interactions. Because our central argument is that people with mild to moderate levels of depression may be particularly sensitive to social information because that information is relevant to their need to belong, we assessed people's daily sense of belonging. To do this, we measured how close and connected people felt to others, the perceived quality of social interactions, as well as how understood they felt in their interactions. Feeling close, connected, and understood are core features of a sense of belonging (e.g., intimacy, Laurenceau, Barrett, & Rovine, 2005 ; Reis & Shaver, 1988 ).

Study 2 used a more refined methodology. Whereas Study 1 used paper and pencil reports, Study 2 used an internet-based daily report method. Paper and pencil reports are at risk for various compliance errors, such as participants completing more than one day's worth of reports at a time. Completing a report for more than one day increases the risk of retrospective reporting biases. This response pattern would undermine the ecological validity of daily process methods. Using an internet-based daily report method corrects for this potential source of error, as well as data entry errors, by virtue of the fact that participants record their own data on the internet site, which then time/date stamps each report. Reports falling outside of the parameters are deleted from the dataset.

Participants were recruited from undergraduate psychology courses at a large, Midwestern university ( N = 49; M age = 20.0, SD = 3.9; 61% female; 68% European-American), and completed questionnaires and a web-based daily report for 28 consecutive days in exchange for course credit.

The CES-D ( M = 16.1; SD = 8.9; α = .86; 25.9% of the sample exceeded the cutoff score of 17 for mild to severe depression), daily CWB ( reliability = .94) and AWB measures ( reliability = .92) were administered.

Daily Interaction Ratings

Participants rated how close and connected they felt to other people each day from 1 ( Not at All ) to 7 ( Absolutely ), and listed up to four “memorable interactions,” which they rated their quality from 1 ( Extremely Bad ) to 5 ( Extremely Good ). Interactions were also rated on feeling understood from 1 ( Very Little ) to 5 ( A Great Deal ). Ratings were averaged across all reported interactions. Principal axis factor analysis with Promax rotation revealed that all three items loaded on one factor ( eigenvalue = 1.25), supporting their aggregation as an indicator of belonging ( reliability = .92).

Participants completed the CES-D at Time 1, and received instructions to complete internet-based daily reports each night between 7pm and 5am. Participants were told it was extremely important to complete surveys during the timeframe we provided for them, to only complete reports for a single day at a time, and that we would only retain daily reports completed during the timeframe we provided. Participants were reminded to complete their daily reports under these conditions in subsequent emails. Only responses time/date-stamped between these times were retained.

The data consisted of 1,124 valid daily reports nested within 49 participants, structured as in Study 1. Participants reported mean daily CWB of 14.8 ( SD = 2.9), which is above the midpoint of 12, and mean daily AWB of 0.9 ( SD = 1.2). Descriptive statistics were very similar to Study 1 for CWB; reports of AWB reflected a larger balance in favor of positive emotions, and greater variability, perhaps as a function of the 28-day timeframe. Participants' belonging scores ( M = 15.9, SD = 3.4) were above the midpoint of 13, indicating a moderately high sense of belonging in daily interactions. According to the intraclass correlation calculations, 41.9% of the variance in daily belonging scores is due to stable, dispositional factors rather than fluctuating daily factors. As in Study 1, more variance was due to stable factors for CWB (61.1%) than for AWB (47.3%).

Depressive symptoms were inversely related to daily CWB (γ = −1.35, SE = .36, t (49) = 3.72, ES r = .35, p < .001), AWB (γ = −.57, SE = .13, t (49) = 4.30, ES r = .40, p < .001), and belonging (γ = −.81, SE = .34, t (49) = 2.39, ES r = .23, p < .05). The focus of Study 2 was on the role of depressive symptoms in moderating the relation between sense of belonging and CWB and AWB ( Table 2 ). To examine this, we created multilevel models for both outcomes (CWB and AWB) in which outcomes were predicted by daily belonging at Level 1 (γ10), with depressive symptoms as a Level 2 moderator (γ01 and γ11). Across participants, feeling a sense of belonging robustly predicted greater daily CWB and AWB, γ(10). In accordance with the results from Study 1 and our hypotheses, people with greater depressive symptoms reported stronger positive relations between a sense of belonging and daily CWB ( Figure 1B ), with a trend toward a significant effect for AWB, γ(11). 3

In line with previous research showing that people with greater depressive symptoms feel that they experience worse social interactions (e.g., Nezlek et al., 2000 ), Study 2 found that people with greater depressive symptoms reported less satisfaction of their need to belong. Study 2 also provided the first indications that depressive symptoms sensitize people to this subjective sense of belonging. On days when people with greater depressive symptoms did feel a sense of belonging, their pattern of responses demonstrated heightened reward and punishment reactions to social interactions. A strong resemblance exists between the moderation results from Study 1 ( Figure 1 ), which used a paper and pencil method and an a priori list of objective social interactions, and results from Study 2 ( Figure 2 ), which used a more rigorous internet-based method with time and date stamping of entries and a measure of perceived belonging during interactions. Also as in Study 1, the effects were stronger for CWB than for AWB, suggesting that people with greater depression symptoms view their lives as more satisfying and meaningful when they have positive social experiences, with less of an effect on positive or negative affect than other people.

Depressive symptom severity moderates relations between sense of belonging and daily cognitive well-being (Study 2).

General Discussion

Across two daily process studies, people with greater depressive symptoms reported a higher number of negative social interactions and a lesser sense of belonging in social interactions. In accord with previous research (e.g., O'Neill et al., 2004 ; Zautra & Smith, 2001 ), we found that compared to less depressed people, people with greater depressive symptoms experienced less well-being on days when they had negative social interactions (heightened reactivity). These studies also extended previous research, demonstrating that although people with greater depressive symptoms experienced fewer positive social interactions (e.g., Joiner & Coyne, 1999 ; Nezlek et al., 2000 ), they were more reactive to their occurrence (i.e., greater reward responsiveness). Previous daily diary studies have shown that people with greater depressive symptoms report more strongly enhanced well-being on days when they experience positive life events ( Nezlek & Gable, 2001 ). The present studies are the first to focus on social life events and feelings of belonging, as well as the first to extend the measurement of well-being to include meaning, purpose, and satisfaction in life. We used a strategy of assessing both objective positive and negative social interactions (Study 1) and appraisals of the quality of social interactions (Study 2). The present studies used multiple measures to assess the latent construct of belonging that is thought to motivate human behavior (Baumeister & Leary, 1995). Thus, it is with some confidence that we can say that belonging plays an important role in how people with greater depressive symptoms derive well-being from social experiences, whether objectively or subjectively assessed. Specifically, people with greater depressive symptoms reacted with more intense positive life evaluations and more positive affect balance in response to feeling a sense of belonging with others.

Results from both studies were stronger for cognitive well-being (judgments of meaning in life, life satisfaction) than for affective well-being (positive and negative affect balance). Meaning in life concerns people's judgments about whether or not their lives make sense and are endowed with a mission or purpose (e.g., Steger, Frazier, Oishi, & Kaler, 2006 ; Steger, Kashdan, Sullivan, & Lorentz, 2008 ). Life satisfaction concerns people's judgments about whether the conditions of their lives are satisfying and conform to their expectations ( Diener, Larsen, Emmons, & Griffin, 1985 ). Together, these variables gauge higher-order judgments about life as a whole, and would seem to require some amount of perspective-taking. In all analyses, the interaction of depressive symptoms and social interactions were significantly related to such judgments. In contrast, only one of three interactions between depressive symptoms and social interactions were significantly related to affective well-being, which concerns people's prevailing affective states over the course of a day. This pattern suggests that for people with greater depressive symptoms, social interactions influence cognitive well-being appraisals more consistently than affective well-being appraisals. Thus, compared to people with lesser depressive symptoms, people with greater depressive symptoms appear to appreciate their lives more when they meet their need to belong.

We derived our hypotheses by extending socio-evolutionary ideas about how mild to moderate depressive symptoms operate in the social world. In our expansion of such models (e.g., Allen & Badcock, 2003 ; Gilbert, 1992 , 2006 ), we drew on the idea that depressive symptoms serve as a warning signal, directing people's limited attentional resources to their current social status and the potential danger of possible rejection by other people. At low levels, depressive symptoms may help people adaptively regulate their social interactions to maintain social value and belonging. However, at greater levels of depressive symptoms, this social value warning system may become hypersensitive, leading to distress and impairment. Previous work on socio-evolutionary models has focused exclusively on negative interactions as signals of looming rejection; our extension pointed to the importance of positive relations as signals of rising belonging. For example, positive social interactions, particularly when a sense of belonging is felt, suggest to a person that his or her social value is high enough to feel safe and secure, allowing movement away from submissive or defensive postures to more active and exploratory motivational states. Our results provided support for these predictions, bolstering the notion that people with subthreshold levels of depression may be particularly attentive to, and benefit more from, positive social interaction and suffer more from negative social interactions compared with people without emotional disturbances.

When considering models informed by evolutionary theories, it is important to note that a distinction is often made between adaptations that provided survival advantaged to humans in our long-passed ancestral environments and the manner in which they function among contemporary life (e.g., Allen et al., 2004 ). That is, depressive symptoms may have developed to help ancestral humans respond to social cues by modulating their activity in ways that would have been appropriate under much more hazardous and precarious circumstances. Ancient adaptations that evolved in response to particular challenges may not be advantageous in our modern environments.

Positive social interactions are probably an encouraging sign for people struggling with depressive symptoms. These interactions might reinforce the idea that they matter to others, counteract the more frequent negative interactions they experience, and provide a tonic for depressive thoughts and emotions. It also may be the case that heightened reactivity – gaining enhanced well-being from these positive social experiences – may signal excessive attachments and vulnerability among depressed people. Their daily levels of well-being may be more “fragile,” subject to the caprices of their daily encounters with others rather than more stable sources of psychological health (see also Gable & Nezlek, 1998; Roberts & Monroe, 1994). Such a possibility fits with some research on sociotropic depression, which finds that sociotropic people are nurturing with relative strangers, but more vindictive in closer relationships ( Sato & McCann, 2007 ). It is not clear from the present data whether people were having the majority of their social interactions and feelings of belonging in the context of very close or less close relationships. It is possible that interactions with relative strangers were providing most of the boost in well-being, which would be similar other reports ( Sato & McCann, 2007 ). People who over-invest in new relationships and neglect or damage closer, more enduring relationships are likely to erode their long-term social resources, which are considered vital to continued functioning (e.g., Baumeister & Leary, 1995; Deci & Ryan, 2000 ).

Alternatively, heightened reactivity may indicate potentially potent everyday interventions. Behavioral activation interventions encourage patients to engage in a greater ratio of healthy behavior with the potential for positive psychological, social, and physical benefits (e.g., Hopko, Lejuez, Ruggiero, & Eifert, 2003 ). In the context of social activity, this means decreasing exposure to situations in which patients attempt to elicit sympathy and patronizing concern from others – reinforcing unhealthy depressive behavior, and increasing exposure to situations in which the patient is provided with genuine social support and acceptance – reinforcing healthy and adaptive social behavior ( Hopko et al., 2003 ). Research on depressive rumination supports this hypothesis. Although frequent ruminators are more likely to seek support and assurance, which can lead to rejection, they respond with greater reductions in distress upon receiving social support and other demonstrations of social acceptance than non-ruminators ( Nolen-Hoeksema & Davis, 1999 ).

There is the possibility, however, that the social interactions that give rise to feelings of belonging among people with greater depressive symptoms are the same ones that reinforce unhealthy depression sustaining behaviors. For example, although eliciting sympathy from others helps maintain a sense of helplessness and sustains depression, people with greater depressive symptoms may nonetheless desire sympathetic interactions and feel that positive social interactions are those in which they receive sympathy. Thus, they may interpret potentially unhealthy interactions as beneficial. Self-verification theory makes a similar claim in that it proposes that people with greater depressive symptoms may prefer to experience social interactions that are in concordance with their negative self-views. For example people with greater depressive symptoms may prefer to be socially rejected to being socially accepted (e.g., Swann, Wenzlaff, Krull, & Pelham, 1992). Thus, in addition to interpreting social experiences in a more negative light, people with greater depressive symptoms may also prefer negative social experiences and find them to be more familiar, and consistent with their self-views. Such biased social processing could explain the problematic social behaviors of depressed people, such as eliciting rejection and failing to gain acceptance (e.g., Joiner & Coyne, 1999 ).

Counseling Implications

The present findings join the growing body of literature linking depression to social functioning. People with greater depressive symptoms experience less pleasant and rewarding social lives – they report fewer positive interactions and more negative interactions. This situation is exacerbated by their greater reactivity to negative interactions. When working with depressed clients, clinicians should recognize that some part of this bleak, social landscape is created through clients' interpretations of events. This observation is consistent with some of the assumptions underlying therapeutic modalities such as interpersonal process therapy and cognitive therapy (e.g., Butler, Chapman, Forman, & Beck, 2006 ; Hollon, Thase, & Markowitz, 2002 ). In accordance with these approaches, the present findings support paying attention to helping clients revise and rehabilitate their interpretations of social events.

While it is the case that the social lives of people with greater depressive symptoms appear less desirable than those of other people, it is also apparent that when good events occur, they respond more strongly and positively. Clinicians should find support in these results for efforts to encourage depressed clients to seek out and achieve positive social interactions. In addition to the higher levels of well-being associated with such positive interactions, discussing positive interactions in session with a clinician may help clients capitalize on their experience. Clinicians who are actively encouraging and supportive when listening to clients relate their positive social experience may be further enhancing the well-being benefits that may result from such positive social interchange ( Gable et al., 2004 ). Suggestions to increase positive social interactions would be consistent with behavior activation treatments of depression (e.g., Hopko et al., 2003 ), which have strong empirical support. Nonetheless, without consideration of the potential for people with greater depressive symptoms to elicit negative responses and initiate uncomfortable social contact ( Coyne, 1976a , 1976b ), it is possible that encouraging increased social engagement could unintentionally produce increased negative social interaction. Regardless of whether they are positive or negative, the present findings demonstrate that the social lives of our depressed clients warrant considerable attention in session.

Limitations and Future Research

Our results are subject to limitations associated with the self-report methods used in the present investigation. There is the possibility that people systematically represented the quantity and quality of their social interactions in ways related to their level of depressive symptoms. If people with greater depressive symptoms interpret their social interactions more negatively (e.g., Swann et al., 1992), then it would be more difficult to argue that they are more reactive to social interactions in general because people with different levels of depressive symptoms recognize, respond to, and modify their environments in different ways (e.g., Barnett & Gotlib, 1988 ; Joiner & Katz, 1999 ). They would be, in a sense, reacting to different events, making comparisons difficult. In the present research, Study 2 used subjective ratings of belonging, which could be influenced by differing interpretive tendencies among people with different levels of depressive symptoms. The fact that Study 1's results, which were based on an objective list of social interactions, mirror those from Study 2 helps allay these concerns. However, it is still possible that people with greater depressive symptoms construe some interactions as being arguments or disagreements whereas less depressed people might view them as unexceptional, ordinary exchanges (e.g., Zuroff et al., 2007). Regardless, it is far from obvious that such a bias in perceiving relatively neutral events as more negative could account for stronger reactions, just as it does not explain why there would be greater reactivity to positive events.

Despite this limitation, it is important to understand the nature of depression's interaction with the complexities of people's dynamic, naturally-occurring social contexts, of which interpretations and perceptions are an inextricable part. This is the aim of externally valid studies like the present one. On the other hand, it is desirable to pinpoint depression's influence not only on interpretations and perceptions, but also reactivity per se. This is the aim of highly internally valid studies and experimental methods. Previous laboratory studies have used non-interactive stimuli (e.g., positive and negative films or facial expressions), rather than actual, in vivo social interactions to assess information perception and reactivity among more depressed people. One solution to the problem of intermingled perceptions and reactivity might be to expose people with different levels of depressive symptoms to standardized, in vivo social interactions in a laboratory setting, and test whether people with greater depressive symptoms interpret positive social stimuli similarly and whether they react more strongly than less depressed people. For example, during a staged collaborative project, a confederate could provide either positive or negative feedback to participants. We would expect that people with greater depressive symptoms would report more strongly enhanced well-being following the receipt of positive feedback and more strongly degraded well-being following the receipt of negative feedback compared to people with lesser depressive symptoms (although self-verification theories of depression might predict the opposite; see Swann et al., 1992).

There are a number of other limitations related to the measures we used in the present study. First, two of the five positive social interaction items we used in Study 1 focus on romantic interactions (flirting or having good interactions with a steady date). This may further limit the how well Study 1 represents the typical and important social interactions of college student samples. Second, our measure of cognitive well-being focused on meaning in life and life satisfaction. There are undoubtedly other indicators of cognitive well-being that should be included in future research (e.g., self-regulation, optimism). Third, our measure of belonging focused on people's appraisals of specific social interactions, and does not capture the full content of this important construct. Future research should consider using broader measures of global belonging (e.g., positive relationships; Ryff, 1989 ).

Although our sample of people with subthreshold depressive symptoms is appropriate for our extension of recent socio-evolutionary models of depression ( Allen & Badcock, 2003 ), it should be noted that most people in both studies did not meet a criteria of having mild-to-severe depressive symptoms. One strength of the model we presented here is that it regards depressive symptoms as occurring on a continuum; it predicts that sensitivity to social cues should increase in proportion to depressive symptoms, regardless of where they are on the continuum of impairment. Nonetheless, the presence of many people who are not manifesting any significant level of depressive symptoms reduces the degree to which the present studies directly test our proposed model of depression. To explore whether depressive symptoms have a social tuning function even at low levels, it would be valuable to replicate this research in stratified samples of unimpaired, mildly depressed, moderately depressed, and severely depressed people.

Finally, the generalizability of the results of the present investigation is limited by our use of non-clinical samples. Although our findings generally support previous research (e.g., Nezlek & Gable, 2001 ; O'Neill et al., 2004 ; Peeters et al., 2003 ; Segrin & Abramson, 1994 ), it is unclear whether our findings would extend to clinically depressed samples. Rottenberg's (2005) hypothesis of flattened reactions to positive and negative stimuli may be more accurate for clinically depressed samples than for non-clinical samples (although Must et al., 2006 found results more in line with our model). For example, if depressive symptoms accumulate to the degree that they interfere with basic cognitive and perceptual processes, then people with severe depression may not be able to monitor the social cues they receive from others. Daily process studies in clinical samples are needed to clarify the boundary conditions of sensitizing versus dulling effects posited by these alternative models.

Conclusions

By focusing on people's reactivity in their ongoing social environments, we gain a more reliable picture of life as it is lived. The present results suggest that people with greater depressive symptoms appear to find greater satisfaction and meaning in their lives when they meet their need to belong, suggesting an important role for positive social relationships in buttressing these important cognitive perspectives on life. Thus, the full spectrum of social interactions may provide especially fertile ground for continued research on etiology, maintenance, recovery, and relapse in depression.

Depression, belonging, and well-being, Study 2.

Acknowledgments

The authors wish to thank four anonymous reviewers and the Action Editor for their suggestion for improving this paper.

Todd B. Kashdan was supported by National Institute of Mental Health grant MH-73937.

Publisher's Disclaimer: The following manuscript is the final accepted manuscript. It has not been subjected to the final copyediting, fact-checking, and proofreading required for formal publication. It is not the definitive, publisher-authenticated version. The American Psychological Association and its Council of Editors disclaim any responsibility or liabilities for errors or omissions of this manuscript version, any version derived from this manuscript by NIH, or other third parties. The published version is available at www.apa.org/pubs/journals/cou .

1 The temporal stability of the CES-D is important to the present study because the CES-D was administered at the end of the three-week diary period. Moderately strong test–retest reliability has been reported over a 2- to 8-week period ( r' s from .51 to .67) and over a 3- to 12-month period ( r' s from .32 to .54) ( Radloff, 1977 ). Thus, CES-D scores appear stable enough for the present study. Concerns over when the CES-D was administered also can be allayed somewhat because of the similarity of results from Study 1 (CES-D administered after the daily reports were collected) and Study 2 (CES-D administered before the daily reports were collected).

2 To investigate the possibility that there was a range restriction in the number of positive and negative social interactions reported by people with lesser and greater depressive symptoms, we split the sample into a Low Depression group (scoring 16 or lower on the CES-D) and a High Depression group (17 or higher on the CES-D). The Low and High Depression groups reported an absence of positive social interactions at similar rates (38.9% of days without a positive social interaction for the Low Depression group versus 40.9% of days for the High Depression group). However, the differences were larger for negative social interactions. Whereas the High Depression group reported 67.0% of days without having any negative social interactions, the Low Depression group reported 84.4% of days without having any negative social interactions. Thus, analyses for people with low levels of depressive symptoms are based on less than 16% of the total number of days. This may have attenuated the magnitude of the associations between negative social interactions and well-being, particularly among those low in depressive symptoms. If this was the case, it might result in an over-estimate of the influence of depressive symptoms on reactions to negative social interactions, although this does not appear to be a problem for positive social interactions.

3 We repeated these analyses for both Study 1 and Study 2 separating positive affect and negative affect into distinct dependent variables. In Study 1, the pattern of results was the same: both positive and negative social interactions significantly predicted Positive Affect and Negative Affect, separately, with depressive symptoms significantly moderating the influence of positive social interactions (but not negative social interactions). In study 2, belonging was significantly, directly related to both Positive Affect and Negative Affect, but this relation was only significantly moderated by depressive symptoms with regard to Positive Affect. This split in outcomes is probably what is driving the merely marginally significant moderating influence of depression in Study 2. If this pattern of findings was replicated in future research, it could indicate the possibility that depressive symptoms sensitize people to positive social events by increasing positive affective reactions, as opposed to dampening negative affective reactions.

Contributor Information

Michael F. Steger, Colorado State University.

Todd B. Kashdan, George Mason University.

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Does using your brain more at work help ward off thinking, memory problems?

The harder your brain works at your job, the less likely you may be to have memory and thinking problems later in life, according to a new study published in the April 17, 2024, online issue of Neurology ® , the medical journal of the American Academy of Neurology. This study does not prove that stimulating work prevents mild cognitive impairment. It only shows an association.

"We examined the demands of various jobs and found that cognitive stimulation at work during different stages in life -- during your 30s, 40s, 50s and 60s -- was linked to a reduced risk of mild cognitive impairment after the age of 70," said study author Trine Holt Edwin, MD, PhD, of Oslo University Hospital in Norway. "Our findings highlight the value of having a job that requires more complex thinking as a way to possibly maintain memory and thinking in old age."

The study looked at 7,000 people and 305 occupations in Norway.

Researchers measured the degree of cognitive stimulation that participants experienced while on the job. They measured the degree of routine manual, routine cognitive, non-routine analytical, and non-routine interpersonal tasks, which are skill sets that different jobs demand.

Routine manual tasks demand speed, control over equipment, and often involve repetitive motions, typical of factory work. Routine cognitive tasks demand precision and accuracy of repetitive tasks, such as in bookkeeping and filing.

Non-routine analytical tasks refer to activities that involve analyzing information, engaging in creative thinking and interpreting information for others. Non-routine interpersonal tasks refer to establishing and maintaining personal relationships, motivating others and coaching. Non-routine cognitive jobs include public relations and computer programing.

Researchers divided participants into four groups based on the degree of cognitive stimulation that they experienced in their jobs.

The most common job for the group with the highest cognitive demands was teaching. The most common jobs for the group with the lowest cognitive demands were mail carriers and custodians.

After age 70, participants completed memory and thinking tests to assess whether they had mild cognitive impairment. Of those with the lowest cognitive demands, 42% were diagnosed with mild cognitive impairment. Of those with the highest cognitive demands, 27% were diagnosed with mild cognitive impairment.

After adjustment for age, sex, education, income and lifestyle factors, the group with the lowest cognitive demands at work had a 66% higher risk of mild cognitive impairment compared to the group with the highest cognitive demands at work.

"These results indicate that both education and doing work that challenges your brain during your career play a crucial role in lowering the risk of cognitive impairment later in life," Edwin said. "Further research is required to pinpoint the specific cognitively challenging occupational tasks that are most beneficial for maintaining thinking and memory skills."

A limitation of the study was that even within identical job titles, individuals might perform different tasks and experience different cognitive demands.

The study is supported by the National Institutes of Health.

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Materials provided by American Academy of Neurology . Note: Content may be edited for style and length.

Journal Reference :

• Trine H. Edwin, Asta K. Håberg, Ekaterina Zotcheva, Bernt Bratsberg, Astanand Jugessur, Bo Engdahl, Catherine Bowen, Geir Selbæk, Hans-Peter Kohler, Jennifer R. Harris, Sarah E. Tom, Steinar Krokstad, Teferi Mekonnen, Yaakov Stern, Vegard F. Skirbekk, Bjørn H. Strand. Trajectories of Occupational Cognitive Demands and Risk of Mild Cognitive Impairment and Dementia in Later Life . Neurology , 2024; 102 (9) DOI: 10.1212/WNL.0000000000209353

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Can aspirin help protect against colorectal cancers?

A new study details how a daily dose could prevent or delay the progression of the world’s third most common type of cancer.

Aspirin is well known for its ability to ease pain from muscle aches and headaches; it reduces fevers; and low doses can thin blood, reducing the chance of clots that cause strokes and heart attacks. Now a new study suggests it may also play a role in colorectal cancer prevention.

Colorectal cancer, a cancer of either the large intestine or rectum, is the third most common type of cancer, and the second most common cause of death from cancer , worldwide. There were 1.9 million new cases diagnosed across the globe in 2020, according to the World Health Organization, and these numbers are expected to grow. In the United States, the rates of colorectal cancers have been rising in people younger than age 50 since the 1990s, which includes more young people dying from the disease, according to the National Cancer Institute .  

Now a new study published in the journal Cancer shows that colorectal cancer patients who took a daily dose of aspirin had a lower rate of metastasis to the lymph nodes and stronger immune response to their tumors. The research suggests that aspirin may be boosting the ability of the immune system to hunt for cancer cells.  

“It is a rather unexpected effect, because aspirin is mainly used as an anti-inflammatory drug,” says Marco Scarpa, a researcher at the University of Padova, and one of the authors of the study. As Scarpa notes, this study suggests that aspirin may be playing a slightly different role by stimulating the immune system’s surveillance response, which can then prevent or delay the progression of colorectal cancer.  

Your immune system is always surveilling the body for cells that just aren’t right. When they find such cancer cells, they will kill them just as they would kill invading bacteria or viruses, says Cindy Kin , a surgeon at Stanford University, who specializes in colon and rectal surgery.  

“The data about aspirin and cancer is really evolving,” says Maen Abdelrahim , an oncologist at Houston Methodist Hospital, who specializes in treating colorectal cancers. However, there are still a lot of unanswered questions about how aspirin can prevent and delay the progression of these cancers, as well as which subset of patients would benefit from a daily aspirin.  

( Colon cancer is rising among young adults. Here are signs to watch for. )

People who take a consistent use of aspirin have a lower risk of colorectal cancer, “but it has to be balanced with the risks,” which includes the possibility of bleeding in the gastrointestinal tract, says Jeff Meyerhardt , an oncologist and co-director of the Colon and Rectal Cancer Center at the Dana-Farber Cancer Institute, in Boston.  

Aspirin protects against colorectal cancer

There are several studies that suggest a link between aspirin and colorectal cancer prevention and delay. However, the mechanism by which aspirin does this is still unknown. That makes it hard to predict which patients will benefit the most.  

In a 2020 meta-analysis , which analyzed the results of 45 observational studies, researchers found that regular aspirin use was associated with less incidence of colorectal cancer.  

A low dose, between 75 and 100 milligrams, was associated with a 10 percent reduction in the risk of developing colorectal cancer; a regular dose of 325 milligrams was associated with a 35 percent decline.  

Other studies have shown a link between daily aspirin and a delayed progression , including a lower risk of dying in patients who had already been diagnosed with colorectal cancer.  

“What has been seen in multiple studies for colorectal cancers is that having a more robust immune reaction does seem to have a better outcome,” Meyerhardt says. “This is looking at how aspirin may interact with that.”  

Study suggests mechanism

In the study, researchers obtained tissue samples from 238 patients who had undergone surgery for the colorectal cancers. Of these patients, 12 percent were taking a daily low dose of aspirin for the prevention of heart disease. When compared to patients who were not taking aspirin, the researchers found a lower rate of metastasis to the lymph nodes, and higher numbers of immune cells that had infiltrated the tumors.  

This higher level of infiltration is thought to be linked to slower cancer progression—including the lower rate of spread to the lymph nodes—by allowing immune cells to enter the tumor mass and fight the cancerous cells more effectively.  

( Why is stomach cancer rising in young women? )

The researchers also found higher levels of immune markers that are responsible for triggering the immune system surveillance response. “It’s boosting the immune system, and it’s helping the immune system inside the tumor,” Abdelrahim says.  

In recent years, the immune system’s role in protecting against the development of cancer has become recognized.  

Patients with suppressed immune systems are at higher risk for developing cancers , compared to patients with a fully functional immune system. As these results suggest, aspirin may increase the vigilance of the immune system when it comes to the detection of colorectal cancers.  

“Your immune system is doing all of these things in the background, that you’re not even aware of,” Kin says. “It’s not just the tumor’s behavior and how aggressive it’s going to be, but it’s your body versus the tumor.”  

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