a research on the subject

Defining Research with Human Subjects

A study is considered research with human subjects if it meets the definitions of both research AND human subjects, as defined in the federal regulations for protecting research subjects.

Research.  A systematic inquiry designed to answer a research question or contribute to a field of knowledge, including pilot studies and research development.

Human subject:  A living individual about whom an investigator (whether professional or student) conducting research:

• Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or
• Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.

The following sections will explain some of the words in the previous definitions.

The regulatory language:

A systematic inquiry designed to answer a research question or contribute to a field of knowledge, including pilot studies and research development.

The explanation:

Understanding what constitutes a systematic inquiry varies among disciplines and depends on the procedures and steps used to answer research questions and how the search for knowledge is organize and structured.

Pilot Studies and Research Development

Pilot studies are designed to conduct preliminary analyses before committing to a full-blown study or experiment.

Research development includes activities such as convening a focus group consisting of members of the proposed research population to help develop a culturally appropriate questionnaire.

Practical applications:

• You are conducting a pilot study or other activities preliminary to research; or
• You have designed a study to collect information or biospecimens in a systematic way to answer a research question; or
• You intend to study, analyze, or otherwise use existing information or biospecimens to answer a research question.

Human Subjects

Human subjects are living individuals about whom researchers obtain information or biospecimens through interaction, intervention, or observation of private behavior, to also include the use, study, and analysis of said information or biospecimens.

Obtaining, using, analyzing, and generating identifiable private information or identifiable biospecimens that are provided to a researcher is also considered to be human subjects.

To meet the definition of human subjects, the data being collected or used are about people. Asking participants questions about their attitudes, opinions, preferences, behavior, experiences, background/history, and characteristics, or analyzing demographic, academic or medical records, are just some examples of human subjects data.

• Interacting with people to gather data about them using methods such as interviews, focus groups, questionnaires, and participant observation; or
• Conducting interventions with people such as experiments or manipulations of subjects or subjects' environments; or
• Observing or recording behavior, whether in-person and captured in real time or in virtual spaces, like social media sites (e.g., Twitter) or online forums (e.g., Reddit); or
• Obtaining existing information about individuals, such as students’ school records or patients’ health records, or data sets provided by another researcher or organization.

Interactions and Interventions

Interventions are manipulations of the subject or the subject's environment, for example is a behavioral change study using text messages about healthy foods.

Interactions include communication or interpersonal contact between investigator and participant.

A study may include both interventions and interactions.

Interactions and interventions do not require in-person contact, but may be conducted on-line.

Private Information

Private information  includes information or biospecimens: 1) about behavior that occurs in a context in which an individual can reasonably expect that no observation or recording is taking place; 2) that has been provided for specific purposes by an individual; and 3) that the individual can reasonably expect will not be made public (for example, a medical record).

Private information must be individually identifiable (i.e., the identity of the subject is or may readily be ascertained by the investigator or associated with the information) in order for the information to constitute research involving human subjects.

The regulations are clear that it is the subjects’ expectations that determine what behaviors, biospecimens, and identifiable information must be considered private. Subjects’ understanding of what privacy means are not universal, but are very specific and based on multiple interrelated factors, such as the research setting, cultural norms, the age of the subjects, and life experiences. For example, in the United States, health records are considered private and protected by law, but in some countries, health information is not considered private but are of communal concern. 

Identifiable Information

The identity of the subject is associated with the data gathered from the subject(s) existing data about the subjects. Even if the data (including biospecimens) do not include direct identifiers, such as names or email addresses, the data are considered identifiable if names of individuals can easily be deduced from the data.

If there are keys linking individuals to their data, the data are considered identifiable.

Levels of Review

Not all projects that meet the definition of research with human subjects need review by the actual committee. For example, projects that pose  negligible risk to participants may be reviewed and recommended for approval by IRB staff ; other projects may need to undergo review and approval by at least one member of the IRB committee or a quorum of the full board. Determination as to the need for review should always be made by the IRB staff.

Examples of Studies That MAY Meet the Definition of Research with Human Subjects

The following examples will likely require further consultation with an IRB staff member.

Analysis of existing information with no identifiers

If researchers have no interaction with human subjects, but will be conducting a secondary analysis of existing data without individual identifiers, the analysis of those data may not be research with human subjects. 

Expert consultation

Key words in the definition of a human subject are "a living individual about whom" a researcher obtains, uses, studies, analyzes, or generates information. People can provide you information that is not about them but is important for the research. For example, a researcher may contact non-governmental organizations to ask about sources of funding.

Program evaluations and quality improvement studies

Program evaluations are generally intended to query whether a particular program or curriculum meets its goals. They often involve pre- and post-surveys or evaluations.

Some program evaluations include a research component. If data are collected about the characteristics of the participants to analyze the relationship between demographic variable and success of the program, the study may become research with human subjects.  Research question:  Are there different learning outcomes associated with different levels of participant confidence?

Classroom research

Classes designed to teach research methods such as fieldwork, statistical analysis, or interview techniques, may assign students to conduct interviews, distribute questionnaires, or engage in participant observation. If the purpose of these activities is solely pedagogical and are not designed to contribute to a body of knowledge, the activities do not meet the definition of research with human subjects. 

Vignettes: Applying the Definitions

Art in Cambodia

An art history student wants to study art created by Cambodians in response to the massacres committed by the Khmer Rouge. The art she will study includes paintings, sculpture, video, and the performing arts.

Much of the research will be archival, using library and online resources. In addition, she will visit Cambodia. While there, she will speak with several museum curators for assistance locating and viewing art collections related to the massacres.

Is this research with human subjects?

No. Although the student will speak with curators, they are not the subjects of her research and she is not interested in learning anything about them. They will, in effect, serve as local guides.

What would make the study research with human subjects?

The student interviews people as they interact with art to understand the role of the arts in evoking and/or coming to terms with traumatic past events. She interviews people who view the art, such as visitors to museums, and discusses what the art means to them. She may collect information about their experiences during the genocide and compare those experiences with their reactions to the art. 

Bank-Supported Micro-Finance in Chile

A researcher is interested in the practice of microfinance in the Chilean Mapuche community. She meets with bankers and asks about the criteria for granting loans, the demographics of the people who receive loans, the types of businesses to which the bank prefers to grant loans, how many loans they give, the payback rates, and other data about the bank’s loan practices.

No. Although the researcher is interviewing bankers, the bankers are only providing information about their banking practices and are not providing any information about themselves. The questions are about “what” rather than “about whom.” The bankers are not human subjects. This type of interview is sometimes referred to as expert consultation.

The researcher explores the impact of small loans, both intended and unintended, on the recipients of the loans. The researcher interviews the recipients of the loans and gathers information from them about their lives before and after they received funding, how the loans affected their relationships with family members and other community members, the impact of the loans on their aspirations, and so on. He asks “about whom” questions designed to understand the impact of micro-loans.

Developing Teaching Materials

A researcher goes to a country in which the infrastructure has been severely damaged to help rebuild schools. The student interviews community members about what curricular materials they need, develops some materials, and teaches a math class.

No. Although interviews are conducted, the intent of interviewing is to assist in resource development rather than answer a research question designed to contribute to a field of knowledge.

If the researcher does pre- and post-testing to assess student learning in his class, is this research with human subjects?

No. The intent is to find out if the materials are effective. This is sometimes referred to as program assessment.

What would make this research with human subjects?

The researcher studies the impact of nutrition and personal variables on learning. He assesses the nutritional composition of the local diet, assesses students’ general health, and compares those data with test scores. He also measures motivation, family composition, and other characteristics of the students using written questionnaires.

Water Conservation

A researcher wants to find out if the campus water conservation program is effective. She will gather some information about water volume usage from the University engineering department. She will also survey residential students about their water usage habits over the last six months, their perceptions of the campus drought education program, and their reactions to the incentives offered by the program (water-saving competitions, free water-saving devices, etc.) She will report her findings to the program’s steering committee and administrators.

No. Although the researcher will systematically survey other students and will be collecting information about them, her intention is to assess the effectiveness of the conservation program.

The researcher designs an online survey to collect information that may help understand factors that influence the residential students’ responses to the conservation program. She asks questions about green attitudes and behaviors, positions on social and political issues, as well as motivation and narcissism.

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What Is Human Subjects Research?

Department of Philosophy, Dalhousie University

• Published: 15 December 2020
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This chapter provides an overview of the nature, scope, and practice of human subjects research. It begins by tackling the general question, “What is research?” Attempts to answer this question typically define research by its methods and/or goals, and the chapter surveys the limits of these definitions through discussion of tough boundary cases. Along the way, the chapter describes various methods (quantitative, qualitative) and types of human subjects research (clinical, social scientific, etc.). The second section of the chapter investigates who is referred to by the language of “human subjects”: which humans tend to be selected as research participants, where human subjects are located globally, and how these locations are changing. The chapter also raises questions about which subjects are considered human in this context, for instance, whether definitions include embryos, cadavers, or stem cells. Throughout, the chapter highlights the ethical issues raised by the various types of activities and subjects described.

Which of the following is human subjects research?

A clinician conducts a placebo-controlled, double-blind, randomized trial of a new treatment for depression.

A sociologist conducts a series of in-depth interviews with paramedics and firefighters about their experiences of burnout, which are then transcribed and analyzed for common themes.

On the basis of published research indicating a reduction of adverse events, a hospital administrator implements mandatory surgical checklists in one of their operating rooms and tracks the outcomes compared to the hospital’s other operating rooms; the administrator hopes that the expected positive results will help to convince reluctant hospital staff to adopt surgical checklists.

A team of economists selects three cities, sends invitation letters to all low-income citizens in those selected cities, and then partners with local government to provide a basic income to selected individuals for three years, tracking a range of health and life outcomes.

A patient seeks care from a family physician for a rare heart condition; after several unsuccessful treatments, the physician tries an unusual combination of medications, and the patient reports feeling much better.

Same as example 5, but the physician then writes up the case for publication in a peer-reviewed medical journal.

A pediatric oncologist offers patients with an otherwise untreatable form of cancer the option to try promising new treatments that are in the earliest stages of development.

Medical students manipulate human embryos in order to learn how to extract cells for genetic tests.

A geneticist analyzes and sequences the DNA from blood samples collected decades ago from the members of a marginal population.

If you found yourself struggling to decide which of these counts as human subjects research, you are not alone: experts and newcomers to research ethics alike find this task difficult. In fact, even highly respected regulatory bodies and authors of codes of ethics struggle to articulate clear and consistent answers to this question (for examples, see the opening chapters in this handbook). And because an affirmative answer to the question is thought to determine which activities are in need of prospective ethics review, the stakes of this debate are thought to be quite high.

The difficulty of this task persists for many reasons but, in particular, because both key concepts in the question—“research” and “human subjects”—are hard to define and plagued by tough, and ever-evolving, boundary cases. In what follows, I will outline these controversies and investigate whether there might be a clear sorting mechanism for the kinds of cases just outlined. For both concepts (“research” and “human subjects”), I will show that a clear definition is hard, if not impossible, to find. But this may not be as big a problem as it seems. In order to explain why not, I will explore a common underlying assumption about the high stakes of this assessment: the presumed connection between ethics and a particular type of regulatory review in human subjects research. Clarifying this relationship will help to defuse the worry about demarcation criteria for these concepts.

What is research? This is a harder question to answer than one might expect: any answer is in danger of being either underinclusive (for instance, by focusing narrowly on medical research when similar activities are carried out by researchers in other disciplines or professions) or overinclusive (labeling everything vaguely experimental or involving human interaction as research). The Tri-Council Policy Statement (TCPS 2) in Canada begins with a reflection on the broad range of practices and activities that qualify as research, before proposing a definition:

The scope of research is vast. On the purely physical side, it ranges from seeking to understand the origins of the universe down to the fundamental nature of matter. At the analytic level, it covers mathematics, logic and metaphysics. Research involving humans ranges widely, including attempts to understand the broad sweep of history, the workings of the human body and the body politic, the nature of human interactions and the impact of nature on humans—the list is as boundless as the human imagination. For the purposes of this Policy, research is defined as an undertaking intended to extend knowledge through a disciplined inquiry and/or systematic investigation . (Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Social Sciences and Humanities Research Council of Canada 2018 , 5, emphasis added)

The ethical guidelines provided by the Council for International Organizations of Medical Sciences (CIOMS) provide a similar (though health-focused) definition and some examples of common research methods:

The term “health-related research” in these Guidelines refers to activities designed to develop or contribute to generalizable health knowledge within the more classic realm of research with humans, such as observational research, clinical trials, biobanking and epidemiological studies. Generalizable health knowledge consists of theories, principles or relationships, or the accumulation of information on which they are based related to health, which can be corroborated by accepted scientific methods of observation and inference . (2016, xii, emphasis added)

Likewise, according to the original Belmont Report in the United States, “the term ‘research’ designates an activity designed to test a hypothesis, permit conclusions to be drawn, and thereby to develop or contribute to generalizable knowledge ” (National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, 1978, emphasis added).

Note first that each of these definitions would lead to a slightly different assessment of the cases outlined at the beginning of this chapter, so we can’t simply point to regulations to answer our question for us without engaging in further discussion about which regulations are correct. More to the point here, though, we can see that the following concepts tend to arise in definitions of research: scientific methods (observation, hypothesis testing, and/or inference), systematic and/or disciplined inquiry, generalizability, and contributing to knowledge. Research, it seems, is implicitly scientific research . Research is something that scientists do (as contrasted with journalists or celebrities, for instance). This qualification is supported by landmark ethical guidelines such as the original Nuremberg Code, Article 8 of which states, “The experiment should be conducted only by scientifically qualified persons” (Nuremberg Code 1949 , 182). And scientific research involves certain systematic and disciplined methods , which when used properly provide some assurance about the generalizability of results.

Does a focus on the scientific method help to sort the test cases? This seems a promising route since the scientific method is thought to be what makes results more reliable than unsystematic observation and inference, which connects to the aim of producing knowledge. The difficulty is that there are many different methods used by researchers in a range of disciplines. Each research method aims to answer a different question—some are comparative, while others try to find out why someone holds a position or acts a certain way.

Qualitative research methods involving human subjects range from those involving close contact and communication between researchers and individual subjects, which are often open-ended and dynamic, such as ethnographic studies, oral histories, narrative inquiries, focus groups, and minimally structured interviews, to more structured and less dynamic methods such as large-scale surveys and structured interviews. Qualitative research is excellent at answering “why” and “how” questions and much less focused on reporting numerical results than quantitative research. As such, it plays an important and complementary role to quantitative research: a quantitative study may determine that some percentage of elementary school teachers report feeling burned out, for instance, while a qualitative study can investigate why this occurring and how it is experienced or understood by those who self-report.

Quantitative research methods involving human subjects include case studies, case series, and n -of-1 studies, all of which focus on the description and analysis of individual cases. They include observational methods such as case–control and cohort studies, which track and compare groups of people over time (either prospectively or retrospectively). In these types of studies, subjects are not assigned to different groups but rather self-select or are otherwise independently sorted into groups (for instance, a study might follow cyclists and non-cyclists). And then there are interventional methods such as randomized controlled trials (RCTs), in which participants are assigned to intervention and control groups randomly, and, when double-blind, neither they nor the researchers involved know which group they were assigned to until the study is completed. In many domains, including economics, public policy, and medicine, the RCT design is regarded as the gold standard of quantitative methods because of its rigorous comparative design and perceived objectivity.

Quantitative clinical research, in particular, proceeds on the basis of positive results in earlier animal studies and then is carried out in phases. Phase I clinical research typically enrolls a small number of healthy subjects (20–80) and aims to determine whether a proposed intervention is safe in humans and at what approximate dose or intensity. Phase II clinical research enrolls a somewhat greater number of subjects (100–300)—this time those with the health condition the intervention aims to treat—and aims to assess both safety and efficacy (the effect under near-ideal conditions). Phase III clinical research enrolls large numbers of subjects (1,000+) and aims to determine whether an intervention is effective. This phase of research is typically the basis for national regulatory approval, meaning that the treatment can be prescribed and sold to patients in some jurisdiction once it has the support of (typically at least two) well-designed phase III trials. Phase IV, or post-marketing trials, track outcomes in the general population once a treatment is widely available.

In both qualitative and quantitative domains, there are meta-level research methods designed to amalgamate the results of research. These include literature reviews, systematic reviews, and meta-analyses. In an effort to reach busy audiences, there are also summaries and syntheses which aim to bring together all research on a given topic and provide an overall assessment. Guidelines for practitioners in medicine often draw upon these meta-level studies, as well as expert opinion, in recommending standards of practice. And the range of methods is always expanding: some newer methods, such as cluster RCTs and umbrella trials, are discussed by Hey and Weijer in this handbook.

Generalizable Knowledge

What this wide range of scientific methods, from in-depth interviews to RCTs, have in common is that they involve a systematic or disciplined effort to produce results that contribute not just to knowledge but to generalizable knowledge —a standard interpretation of this term is “the use of information to draw conclusions that apply beyond the specific individuals or groups from whom the information was obtained” (Coleman 2019 , 248). This brings us to the aims of research, which were a common component of the definitions of research offered earlier. Each of the methods described might be thought of as contributing to generalizable knowledge, while something like trial and error in clinical practice might be aimed only at benefiting an individual patient. In order to figure out whether quality improvement efforts—such as instituting a surgical checklist in one operating room and comparing with others—count as generating generalizable knowledge, we would look to their aim. In the case as I described it at the outset, the administrator believed that they already knew the intervention would be successful at reducing rates of adverse events, based on the research evidence. The aim was to convince the healthcare team in the hospital that these results applied locally so that they would adopt the practice. This seems to be a case where the primary aim is changing local behavior rather than adding to general knowledge. This way of separating quality improvement activities from research proper has become quite popular in recent years. Scholars take different positions on whether this way of settling the matter is successful or not. This debate turns on, among other things, different ideas of what is meant by “generalizable knowledge.”

Most interpretations of “generalizable” focus on the applicability of results to people who were not in a study. But this can be tricky. An RCT with strict criteria for who is included, that tests an intervention against placebo, and that strictly controls the context in which treatment is administered (for instance, only by specialists in a highly resourced urban hospital) may produce results indicating that a particular medical treatment is effective. This sort of clean explanatory RCT is thought by many scholars to be the exemplar of a study design yielding generalizable results. But a rural physician in a low-resource area dealing primarily with elderly patients who have multiple health conditions might not regard the results of the study just described as generalizable to their patients. (And they would probably be right about this—the gap between research evidence and individual patient care is a real one, and closing or narrowing that gap is something researchers have been working on for decades. The advance of pragmatic trials is one attempt to solve this problem, for instance.) Through this example, we see some of the challenges inherent in claims made about generalizability, particularly when interpretations focus on applicability. Not all areas of scientific investigation lend themselves to the production of law-like generalizations of the sort (ostensibly) found in physics or chemistry. And very few medical interventions work for all patients, without qualification. To return to the quality improvement case, there is a sense in which knowledge is gained through the investigation—something new is learned about whether surgical checklists work in this specific location—and the knowledge is intended to generalize—for instance, across other operating rooms in that facility. Is this not (at least locally) generalizable knowledge, then? Many people seem to want to say “no” here but struggle to find a clear rationale for their position.

The challenges encountered thus far in our efforts to define research indicate that a new strategy is in order; accordingly, let’s turn back to our original question—“What is human subjects research?”—and ask why we are seeking an answer to this question. Perhaps the question is ill-conceived, or perhaps our aims will help guide us toward one of these imperfect options or even something better. What are the stakes here? Why does it matter what counts as human subjects research? Why would anyone resist having their actions labeled “research”?

The common answer to this question—the one potential researchers themselves would likely be quick to offer—is that it matters because activities that are considered research involving human subjects must undergo review by a research ethics committee (REC) and secure approval before recruiting any participants. 1 In other words, there are regulations in most jurisdictions requiring that certain types of activities are subject to independent oversight. According to the TCPS 2 in Canada, for instance, “A determination that research is the intended purpose of the undertaking is key for differentiating activities that require ethics review by an REB and those that do not” (Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Social Sciences and Humanities Research Council of Canada 2018 , 14). 2 A common rationale for this is that the primary aim of research is to gather knowledge to benefit people other than those in the study itself. By contrast, clinical practice, which also involves human subjects, is regulated differently (and with much less direct oversight)—by expectations that professionals will adhere to professional norms and guidelines. Because the aim of practice is benefit for the particular patient, it is thought that fewer or at least different ethical concerns arise. Similarly, other professions, like journalism, have their own sets of norms and rules guiding their activities, tied to their specific aims. The special ethical oversight of research activities is relatively new, in historical terms, since national regulations on human subjects research were enacted in most jurisdictions, in response to the public outcry over publicized cases of abuse of research subjects (for more on this, see the opening chapters of this handbook). When these regulations were proposed, those who drafted the regulations were acutely aware of the need to avoid encroaching on other domains of professional activity—particularly clinical practice (Beauchamp and Saghai 2012 ).

From the earliest attempts to offer a research–practice distinction it was clear that there would be troublesome boundary cases. 3 Phase I (or “first in human”) clinical trials—famously, those in pediatric oncology—tend to enroll patients who have cancer (not healthy subjects), and when there is no other treatment option available for that form of cancer, the research looks pretty much identical to practice (Kass et al. 2013 ). These sorts of activities might be thought of as “therapeutic research,” “innovative therapy,” or “unvalidated practice” depending on one’s orientation to the research–practice distinction. Other boundary cases recognized by early scholarship in this area included what would now be considered a type of comparative effectiveness research, in which two widely available treatments are compared to see which performs better, and quality improvement activities, in which healthcare systems experiment with new rules or guidelines in order to see how well they work in local settings (Beauchamp and Saghai 2012 , 49). Note that it is a necessary, not merely accidental, feature of such activities that they are in some sense both research and practice simultaneously. Phase IV studies are also often ambiguous—depending on how rigorously they are designed, they may also look simply like tracking adverse events in clinical practice. So while research has been defined in terms of its distinctive aim, the distinction is fuzzy and contested; and it continues to be plagued by borderline cases. 4

Note also that the way research was defined for regulatory purposes—against medical practice in particular—meant that the resulting distinction tracked the activities of greatest ethical concern in the medical context specifically. But human subjects research is a much broader category than simply medical research: there are a range of ways in which human subjects may be subjects of studies, including, for instance, in social scientific research. Because this type of research is helpful for understanding the stakes of getting the answer to the title question right, I will outline briefly the social scientific backlash to research ethics oversight, which typically involves delays associated with the prospective review of proposed research and some of the ways that ethics regulation has adjusted to accommodate the range of different types of investigations involving human subjects.

Cases from the social sciences are among the more prominent examples of controversial research in the twentieth century: the Milgram experiment on obedience to authority and Zimbardo’s prison experiment with students assigned to the role of prisoner or guard might come to mind (Haggerty 2004 ). Given that the outcry about the abuse of human subjects in medical research happened around the same time in many jurisdictions (roughly the 1970s), it is no surprise that ethics regulations were developed and applied across all domains of research with human subjects, including social science research. Resistance to these regulations is common, particularly (though not uniformly) in the social sciences, where being lumped in with medical researchers strikes many as bizarre overreach: “What began years ago as a sort of safeguard against doctors injecting cancer cells into research patients without first asking them if that was OK has turned into a serious, ambitious bureaucracy with interests to protect, a mission to promote, and a self-righteous and self-protective ideology to explain why it’s all necessary” (Becker 2004 , 415). Becker is referring here to what he calls “ethics creep,” which involves “a dual process whereby the regulatory system is expanding outward to incorporate a host of new activities and institutions, while at the same time intensifying the regulation of activities deemed to fall within its ambit” (Haggerty 2004 , 391).

A common critique raised by social scientists hinges on the inconsistency between the way different professionals, for instance, journalists and academic social scientists, are treated under current regulatory schemes. The very same activity—interviewing people, for instance—seems to trigger extensive and burdensome oversight when conducted by social scientists even though journalists proceed much more freely. In locating the problem with this arrangement, Haggerty draws attention to precisely the problem identified in this chapter, namely that central concepts like research are poorly defined in documents regarding the ethical regulation of research; they are “empty signifiers, capable of being interpreted in a multitude of ways, and occasionally serving as sites of contestation” (2004, 411). Interpretation is required, and because members of RECs feel responsible for protecting people, they tend to take what he calls a “just in case” approach, in which research is interpreted inclusively (and over-broadly) (2004, 411). This means that social scientists may be subject to extensive oversight.

In 2004, Haggerty articulated his concern as follows: “Over time, I fear that the [REC] structure will follow the pattern of most bureaucracies and continue to expand, formalizing procedures in ways that increasingly complicate, hamper, or censor certain forms of non-traditional, qualitative, or critical social scientific research” (pp. 392–393). This has also been referred to as part of the expansion of neoliberal audit culture and identified as part of the increasing bureaucratization of academia (Taylor and Patterson 2010 ). In response to this perceived ethics creep, some social scientists have called for “creative compliance” or even outright resistance to ethics regulations. One option—reclassifying one’s research as performance art (or some other unregulated activity) is offered with a wink, but behind closed doors researchers will sometimes admit using such tactics (Haggerty 2004 , 408). These efforts have in some cases been met with further regulation: “As some of us have tried new dodges to skirt the requirements, the [RECs] have wised up and closed loopholes” (Becker 2004 , 415).

Yet against these dire predictions and in response to the outcry and backlash generated by social scientists in the wake of early, more heavy-handed and medically oriented regulatory approaches, regulations (and their interpretation) have shifted in the opposite direction in many jurisdictions (for an overview of international regulations, see the chapter by Nelson and Forster in this handbook). In Canada, for instance, the most recent version of the TCPS 2 takes a proportionate approach to the review of research:

Given that research involving humans spans the full spectrum of risk, from minimal to significant, a crucial element of REB review is to ensure that the level of scrutiny of a research project is determined by the level of risk it poses to participants. … A reduced level of scrutiny applied to a research project assessed as minimal risk does not imply a lower level of adherence to the core principles. Rather, the intention is to ensure adequate protection of participants is maintained while reducing unnecessary impediments to, and facilitating the progress of, ethical research. (Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Social Sciences and Humanities Research Council of Canada 2018 , 9)

As this statement indicates, while all research is held to the same high ethical standard, research of minimal risk is thought to require a lower degree of oversight. Ethics review in Canada begins with a determination that the activity is in fact research with human subjects; activities described as falling outside of the definition of research include the sorts of quality improvement activities outlined in the hospital administrator case and “creative practice activities” such as those undertaken by artists (p. 19). 5 Next, some activities that meet the definition of human subjects research are automatically exempt from review, including 1) research that relies entirely on legally accessible, publicly available information where the individuals have no reasonable expectation of privacy and 2) exclusively observational qualitative research conducted in public places where there is no reasonable expectation of privacy and individuals are not identified in the written report (pp. 15–18). This will cover much of the research conducted by historians and some observational studies conducted by social scientists, educators, etc.

At this point, if an activity is considered research and not exempt, it may still be afforded an expedited (“delegated”) review if it is low-risk: according to Article 6.12, “In keeping with a proportionate approach to research ethics review, the selection of the level of REB review shall be determined by the level of foreseeable risks to participants: the lower the level of risk, the lower the level of scrutiny (delegated review); the higher the level of risk, the higher the level of scrutiny (full board review)” (p. 79). In delegated review, the committee assigns one member (or some equivalently qualified person) to assess the proposal rather than assessing it all together. A negative assessment at this stage refers the study back to the full committee for review. Because social scientific research is more likely to be minimal-risk than medical research, it is well positioned to benefit from delegated review. Canada is not unique here: similar exclusions and exemptions typically exist in other national regulatory systems. And in some jurisdictions they are even broader: in the United States, for instance, public health surveillance, criminal justice, and intelligence activities are all excluded from the domain of “research” and exemptions (activities requiring only “limited review”) are offered for most interview- and survey-based research, secondary research even when it uses identifiable private information or biospecimens, and “benign behavioral interventions” (Coleman 2019 , 248). This is a more permissive approach, overall, than the one found in Canada, and the trajectory seems to be generally in the more permissive direction over time.

At this point, we have enough background about the relationship between research and regulation to return to our question about the stakes of this discussion: why would someone wish to avoid having their activity labeled research? The answer given by some investigators is that they might resist if they think there are immediate, and burdensome, regulatory implications. A few things can now be said about this. First, it may be the case that there were times and places where the burdens of regulatory oversight were heavy even in the face of minimally risky activities or where the interpretation of regulations was overzealous. But it is unlikely to be true today—most systems have built-in exemptions and expedited processes for these sorts of cases, as the Canadian example makes clear, and discrepancies in interpretation between RECs have had time to resolve. In the face of complaints from researchers, it is good to look closely at the current local regulations and the way they are implemented. Second, in some jurisdictions today there are known inefficiencies in the regulatory oversight system—this occurs for a wide range of reasons but particularly because the process typically relies on volunteer labor and can involve reading hundreds of pages of detailed, technical proposals at a time. As a result, there are sometimes long delays, and researchers are entirely within their rights to complain about this, though they should be careful about selecting an appropriate target of criticism, whether that’s the local REC or the system within which RECs operate. Further, instantaneous processing of files would be unreasonable on the part of researchers, so negotiation will be needed to find a reasonable timeline, given shared goals. 6 Finally, some of the resistance likely arises from a misunderstanding about what ethics is and how it operates in the world. This requires some attention.

For many researchers, regulatory oversight has become synonymous with ethical assessment. You might hear a hint of this when researchers talk about “getting through ethics,” “waiting for ethics,” or claiming to have “completed ethics” once they have received approval from an ethics board for their study. A similar sort of reduction of ethics to a formal process sometimes occurs in contexts where healthcare providers seek informed consent: they may talk about “consenting the patient” in advance of a procedure, for instance, which is typically reduced to having the patient sign a legal document. It is important to appreciate why this position is indefensible—why legal paperwork or regulatory approval isn’t in any meaningful way a substitute for ethics, understood properly.

To begin, consider a study that has received ethics approval and yet which, when it is actually carried out, has risks that are unreasonably high (perhaps most subjects enrolled will die) a flawed design (perhaps it is not possible to achieve statistically significant or otherwise meaningful results), subjects are told they can’t leave the study once enrolled (violating the voluntariness of their ongoing consent), or the particular individuals in the study are easily identifiable in the published final report (violating their privacy). That study is unethical, in spite of having received approval from an ethics committee. Any number of things may have gone wrong here. First, like all human activities, review is fallible, and sometimes committee members will make mistakes. Sometimes the mistake will be in applying the rules, but at other times the mistake might be in the rules themselves. The particular rules applied by any ethics committee are open to debate, discussion, and revisions in light of new developments in scientific or ethical domains. The regular updates to codes of ethics such as the “Declaration of Helsinki,” currently in its seventh revision since 1975, provide some indication of the rate of change in these domains. Second, the researchers may have provided only a general description of certain activities (such as the trial design or informed consent process) in their application to the ethics committee and then, in specifying these matters later on, made poor choices. Third, researchers may simply have deviated from what they promised to do in their application to the ethics board. The research process relies on a certain amount of trust and good will between reviewers and researchers, and this can be violated by unethical or incompetent researchers. Approval by an ethics committee, then, is not all there is to an assessment of whether some activity is actually ethical .

Awareness of this simple fact helps us to see the dangers of thinking that classifying something as research means a particular set of ethical rules applies that wouldn’t otherwise. Codes of ethics aim to identify and articulate ethical principles or rules, and ethics committees do their best to interpret and apply these general principles to particular cases. But whether those committees existed in the middle ground between principles and action or not (and until recently, they didn’t), ethical principles would still apply to certain activities whenever those activities had certain features. Research with human subjects, as noted, aims at generalizable knowledge, and it typically “uses” those subjects to get knowledge. Along the way, the subjects may be made better or worse off, and any interaction where people make others worse off raises ethical concerns about harms such as exploitation and disrespect. Think about the contrast between paradigmatic cases of medical practice and medical research here—in practice, a healthcare provider aims primarily to benefit the patient, while in research, they aim primarily to generate new knowledge. When getting new knowledge requires the use of another person’s body, it seems clear that we’re in risky ethical territory.

Another way of appreciating the scope of ethics as something far bigger than ethics regulations is to think about the fact that regulations won’t specifically state things like “don’t murder your subjects” or “don’t steal the personal belongings of your subjects” because these ethical prohibitions are thought to be covered by existing criminal laws and not in need of restating. There are many ways to be unethical beyond those listed in codes of ethics because those codes are only part of a larger social system.

Further, some of the ethical rules present in codes and guidelines arise because of the place of research within society and not merely because it is a transaction between individuals. Research proceeds only with the cooperation and support of the societies in which it is conducted, which provide funding, regulation, legal protections, social and physical infrastructure, potential subjects, and more. The requirement that research is socially valuable—that it contribute to knowledge on the topic and directly or indirectly benefits society—is one such rule imposed on research with human subjects (you can read more about this requirement elsewhere in this handbook). The requirement that research is scientifically valid—including the expectation that methods are rigorous and results are meaningful—draws on norms of science developed independently by scientists, which prioritize epistemic values such as fruitfulness, scope, and accuracy in theory construction. Scientists are also held to ethical restrictions around activities considered research misconduct, such as plagiarism, fabrication, and falsification, even though these activities aren’t listed explicitly in codes of ethics for research with human subjects.

Professional Ethics

We’ve been discussing, and trying to articulate the problems with, a particular resistance to being labeled research that results from a misunderstanding about how ethics operates in the world. Hopefully the responses to this argument have been convincing thus far. There is, however, a more nuanced version of the position remaining: some investigators might resist the research label because they believe they are governed by codes of ethics developed prior to current codes and articulated within their professions and see the bureaucracy associated with contemporary ethics review as a less nuanced and perhaps even misleading way to go about thinking through the ethical dimensions of their work. They see a perfectly functional self-regulating profession taken over by people with little or no understanding of the nature of their work or the subtle and precise responses to ethical dilemmas they’ve developed over time.

For example, journalists have ethical norms prioritizing the protection of sources—these norms evolved because of social-historical cases where harm arose (in the extreme, people who were killed when they were identified after a story was published) and a recognition of the need to avoid those harms going forward. This ethical rule for journalists is tied to what is valuable about the activity (here: truth) and a recognition of particular harms that could arise in telling the truth (here: people who assisted in exposing the truth could be killed). If you want to proceed with an activity that involves interaction with other people (maybe even in some sense “uses” them to gain knowledge) but in that interaction, or afterward, those people might be harmed, you should probably ask how that harm can be minimized. Responsible professionals in a range of domains have engaged in this thoughtful work for decades and even centuries. Anthropologists, for instance, have been reflecting about the particular ethical duties arising from ethnography since the method was developed, such as the shifting loyalties that result from the close relationships formed during fieldwork, and the desire of state entities to access and direct their research to secure information from enemies during wartime (Fluehr-Lobban 2002 ).

A decisive response to these concerns is unnecessary here: it is sufficient for the purpose of this chapter that we are aware of them. It is a matter of ongoing discussion in a range of human domains whether certain activities should be regulated or not or whether they should be regulated using one set of rules or another. In general, the position taken by liberal democratic states is that professions and industries with a history of serious harm to citizens have forfeited their right to self-regulation. Research on human subjects has a sufficiently sordid history to qualify here. Whether this inappropriately covers social scientists or others will likely be a matter for further debate. For our purposes, what is important is that we recognize that ethical rules apply regardless of which set of regulations is in force (state-imposed external ethics review, professional codes of ethics, or novel alternative oversight mechanisms). So while the stakes of the discussion are high in the sense that they determine this regulatory path, they are not as high as people tend to think because the ethical rules will apply regardless. Being labeled performance art rather than research might mean you avoid filling out some forms, but it won’t on its own change the nature of your ethical obligations since those arise out of the type of activity planned and its aims and consequences.

In sum, the best response we have to the question “What is research?” is probably that research aims to produce generalizable knowledge, but it is important to recognize that this is an imperfect definition and leaves open a range of debates, including those related to the correct interpretation of “generalizability.” It is also important to recognize that answering this question may not be the best way to decide what systems of accountability ought to track the ethical issues that arise in knowledge-gathering activities; it is worth always keeping in mind that a range of regulatory mechanisms are possible. We have also defused some of the anxiety around responses to this question by tracing and responding to some of the reasons for resistance to the label. The ethical principles arising from an activity aren’t invented and dictated by RECs—they apply whether an activity is labeled research or not and whether it is regulated as such or not. There is room for critical engagement here, but at the end of the day there’s just no escaping ethics.

Human Subjects

I have indicated that there is debate over not only what counts as research, as we’ve just seen, but also who is included in our discussions of human subjects. There are two versions of the question “Who are human subjects?,” each of which raises distinct ethical issues. First, we might wonder which humans end up being research subjects. Is there a paradigm or “model human” researchers have in mind? Are there some humans on whom research is forbidden or significantly restricted? Where are human subjects located globally, and how is this changing? Is there a shortage or surplus of human subjects available for research? How many people are research subjects annually? Depending on the answers to these questions, how might we assess the fairness of the burdens and benefits of research participation? This version of the question raises issues about representation in research as well as more general concerns of distributive and social justice.

Second, we might wonder which subjects are included in discussions of human subjects research. Are any of the following included, for instance: fetuses, embryos, brain-dead humans, cadavers, human organs or tissues, reproductive tissues, or stem cells? And, particularly if some of these items are included, why stop at the boundary of the human species? What lies behind the strict demarcation between human and nonhuman animals as subjects of research? Thinking more broadly, what are the implications of various positions on this matter for research on (hypothetical) conscious, sentient robots or aliens? This version of the question raises issues of moral status. I’ll outline both of these sets of issues.

Which Humans?

The human subjects of research have not always been representative of the diversity of humanity or even of the local populations within which research was conducted. The tendency of Western researchers (white men, for the most part), prior to ethics regulations, to seek out vulnerable populations such as prisoners, children at boarding schools, hospital patients, sex workers, citizens of other countries, racial minorities, and impoverished persons (and especially people at the intersection of these categories) for inclusion in research is well documented. The attraction of these groups was precisely their vulnerability—the fact that it was difficult or impossible for them to refuse involvement, for instance. Early responses to this situation focused on protections for variously identified vulnerable populations. While these concerns persist, and took on new life when multinational research became more common in the 1990s, another concern about representation has arisen more recently: the underrepresentation of certain groups in research. While the first set of concerns track disproportionate burdens of research participation, the second set tracks the lost benefits of research participation. The ethical assessment of the former actions—essentially, preying on the vulnerable—is more easily appreciated, so I’ll say a bit about the latter problem. Failing to ensure that subjects are representative of particular groups can lead not only to missed opportunities to benefit those populations but also to direct harm when research is falsely generalized across that group, as when a drug with positive results in one group is dangerous or toxic to another.

Women were underrepresented in clinical research in the United States (and elsewhere) until at least the 1990s. As a result of improved regulations, the United States has shifted toward more equitable inclusion of women in publicly funded clinical trials, though most studies still fail to analyze results by sex/gender in spite of the recognized benefits of doing so (cf. Geller et al. 2018 ). This is a development worth noting, but it is important to keep in mind that this tracks only clinical research, funded publicly, in one country. We shouldn’t assume the underrepresentation of women in human subjects research has been resolved or even that sensible extension to related domains has been made—the selection of exclusively male mice for animal research continued for many years after these changes were made to human subjects regulation and is still the status quo in many countries and contexts (Shansky 2019 ). The attempted justification for these exclusions has been decisively refuted in the literature dozens of times. Addressing one common mistake clearly driven by outdated gender norms, Shansky reminds us, “Women, but not men, are still pejoratively described as hormonal or emotional, which curiously neglects the well-documented fact that men also possess both hormones and emotions” (2019, 825). The resulting imbalance has affected research in many fields that continue to rely on animal studies such as neuroscience, endocrinology, physiology, and pharmacology. As a result of the exclusion of female mice from neuroscience research, and because research in animals provides the foundation for clinical trials, “the current understanding of how to most effectively treat disease in humans is similarly unbalanced” (Shansky 2019 , 825).

Over the past five years, Canadian and American funding bodies have introduced new requirements for researchers to consider sex as a biological variable in animal studies, and similar efforts have been made by the European Commission (Shansky 2019 ). Of course, sex/gender is not the only characteristic that has been unequally distributed in research studies. The same arguments offered in support of ending the exclusion of female animals from animal research and women from clinical research have been marshaled in favor of improving the inclusion of children, pregnant women, and specific ethnic minority groups (for instance, particular indigenous groups in Canada) with limited success. As mentioned, these exclusions have the potential to lead to significant harm to these populations, particularly in clinical practice since interventions never tested on a population may turn out to have more harms than benefits, and the lack of information about effects of treatments in that population might leave clinicians and others uncertain about how best to act even when acting quickly is critical. It may also simply be unjust in its own right to exclude people from research that might benefit them.

In addition to the explicit long-standing exclusion of particular identifiable groups, such as women, researchers have excluded populations indirectly by, for instance, preferring subjects who are healthier, are younger, and have fewer comorbid conditions. One result of these exclusions has been an underrepresentation of elderly people in clinical research. Because underrepresentation in research means the bench-to-bedside knowledge translation gap is bigger, this likely means elderly people are missing out on certain health benefits. And they aren’t the only ones losing out on benefits: clinical research subjects are not generally representative of a large percentage of the patient population for whom the interventions are intended. For instance, Humphreys and colleagues found that “highly cited trials do not enroll an average of 40.1% of identified patients with the disorder being studied, primarily owing to eligibility criteria” (2013, 1030). Other identifiable groups who may be affected by exclusions indirectly are people whose immigration status is uncertain, people who don’t speak the local language, and people who live far from the urban centers where much research occurs. Who is overrepresented in studies, then? People from “Western, Educated, Industrialized, Rich, and Democratic . . . societies” (Henrich, Heine, and Norenzayan 2010 , 61). The 2019 World Health Organization’s World RePORT , drawing on data from 2016, indicates that the recipients of research funding from the top 10 funders globally continue to be mostly institutions and investigators in North America and Europe working on non-communicable diseases (World Health Organization 2019 ).

While this is true today, some things are changing. Though most clinical research (approximately 70 percent) is still conducted in North America and Europe, “significant West-to-East and North-to-South shifts appear to be underway” with researchers looking increasingly to Asia, Africa, South America, and eastern Europe (Sismondo 2018 , 55). One reason this is thought to be happening is that researchers are keen to find countries where the medical system is advanced enough to locate their trials, with access to a large population, but at the lowest cost possible. According to Sismondo, costs per subject in clinical trials are estimated to be 30–50 percent lower in India than in North America or western Europe (2018, 55). Researchers are also interested in finding populations where individuals are not already taking other medications, and countries like India may have a greater proportion of subjects like this (Sismondo 2018 , 54). There are also more altruistic motives: low- and middle-income countries (LMICs) have particular health problems, and some researchers in high-income countries (HICs) may have an interest in helping to alleviate those problems, such as high rates of HIV transmission, epidemics such as the recent Ebola outbreaks, neonatal disorders, and neglected tropical diseases. Research in developmental economics suggests that these motives and effects can also be mixed in quite complicated ways: for instance, aid organizations may seek to alleviate global poverty and design studies to inform this effort but, in doing so, also reinforce the continued existence of their organization, create cycles of dependency, or perpetuate assumptions about the lack of knowledge or expertise in targeted populations.

Another reason for this global shift is that researchers often report difficulty recruiting subjects in HICs. For example, according to McDonald and colleagues ( 2006 , np), for multi-center RCTs funded by two UK funding agencies, “Less than a third (31%) of the trials achieved their original recruitment target and half (53%) were awarded an extension. The proportion achieving targets did not appear to improve over time. The overall start to recruitment was delayed in 47 (41%) trials and early recruitment problems were identified in 77 (63%) trials.” In general, “Recruitment is often slower or more difficult than expected, with many trials failing to reach their planned sample size within the timescale and funding originally envisaged” (McDonald et al. 2006 , np). This shortage of (appropriate) research subjects is of interest to research ethics because it can drive the demographic shifts just described, which raises concerns about potential exploitation of subjects in multinational studies. It also arguably lends further support to the social value requirement of research since a resource shared by all researchers (including industry researchers) is in limited supply: human research subjects. Perhaps this means lower-value research ought not to be conducted, or the bar for what counts as a sufficiently socially valuable study should be raised (Borgerson 2016 ).

The relationship between funders, researchers, and subjects is also of interest to bioethicists. One of the reasons ethical concerns arise in LMICs is that the research is often funded and designed in HICs, and this raises worries about potential exploitation. Another concern arises when the results of the research conducted in LMICs won’t benefit other people in those same populations. One of the reasons given for the increased interest in conducting research in LMICs is that populations are “treatment-naive”—this means in general they don’t have access to healthcare, and they are likely to be unable to afford whatever treatment emerges from the research if it is successful. This feature of multinational research has generated extensive discussion among bioethicists, many of whom now agree that research should be responsive to the health needs of local populations if it is to avoid charges of exploitation. Yet this worrisome overview of the global situation was provided in 2013:

Total global investments in health R&D (both public and private sector) in 2009 reached US$240 billion. Of the US$214 billion invested in high-income countries, 60% of health R&D investments came from the business sector, 30% from the public sector, and about 10% from other sources (including private non-profit organisations). Only about 1% of all health R&D investments were allocated to neglected diseases in 2010. Diseases of relevance to high-income countries were investigated in clinical trials seven-to-eight-times more often than were diseases whose burden lies mainly in low-income and middle-income countries. (Røttingen et al. 2013 , 1286)

Dandona et al. also found that research priorities were misaligned with the health needs of the local population in India specifically: “funding for some of the leading causes of disease burden, including neonatal disorders, cardiovascular disease, chronic respiratory disease, mental health, musculoskeletal disorders and injuries was substantially lower than their contribution to the disease burden” (2017, 309). The gap between funding priorities and disease burden has been of interest to economists, political scientists, and bioethicists alike for many years.

A roughly 70/30 split between industry funding and other sources is common in clinical research. Of the US$1.42 billion spent on health research in India in 2011–2012, “95% of this funding was from Indian sources, including 79% by the Indian pharmaceutical industry” (Dandona et al. 2017 , 309). In the United States, “Principal research sponsors in 2003 were industry (57%) and the National Institutes of Health (28%)” (Moses et al. 2005 , 1333). Even though there seem to be shifts underway toward more industry-sponsored research in the clinical context, practicing physicians are still a vital part of research, often supplying the subjects for research:

Currently, about three-quarters of studies in the United States are conducted in the private sector by non-academic physicians who recruit their own patients or local community members into drug studies. Over 60,000 of these studies take place in the United States each year, accounting for 75 percent of the 80,000 clinical trials conducted worldwide; to execute these studies, more than 50,000 U.S. physicians registered with the Food and Drug Administration (FDA) as principal investigators on one or more clinical trials in 2001. As for the human subjects, 3.62 million Americans participated in pharmaceutical clinical trials in 2003 alone. (Fisher 2009 , 2)

The particular ethical obligations arising from the dual role of physician-investigators, such as the need to balance a commitment to doing what’s best for the patient with an interest in seeking knowledge, have received attention from bioethicists, as have the financial conflicts of interest arising when physicians play not only these two roles but a third role in their relationship to industry sponsors.

Another matter of interest to bioethicists is that there are some people who make a career out of being research subjects. Some of them self-identify as “guinea pigs for hire” and seek participation in phase I studies (on healthy subjects) (Lemmens and Elliott 2001 ). The inclusion of these people in studies raises ethical issues about appropriate compensation (whether wages and benefits or payment), undue inducement (if the payment is thought to be too high), scientific validity (whether people strongly oriented to please researchers so that they may be hired again will be more inclined to deceive researchers, for instance), upper limits of risk for studies under conditions of informed consent, and social justice and fair subject selection (since career research subjects tend to be from particular demographic groups, such as homeless people and students). For more on this issue, see the chapter by Fisher in this handbook.

Finally, a note about the number of research subjects: the research enterprise is massive and enrolls millions of human subjects every year. It is surprisingly difficult to get a clear picture of the enterprise globally (for more on why, see Young et al. 2015 ). Our best estimates come from clinical research: drawing on the 2009 CenterWatch Sourcebook, Sismondo suggests that, while estimates vary widely, there are approximately three to six million subjects involved each year (2018). And these numbers seem to be increasing. If we were able to add in figures from research in the social sciences, these numbers would skyrocket. In fact , you might be a research subject right now : there is ongoing debate over whether the tactics used by social media sites to track and manipulate their users qualify as human subjects research. If they do—and this turns partly on how we settle the issues raised in the first part of this chapter—we might find out that many of us are unwitting research subjects.

Which Subjects?

Who counts as a human subject of research? Codes of research ethics are often inclusive in their definition, for instance: “The World Medical Association (WMA) has developed the Declaration of Helsinki as a statement of ethical principles for medical research involving human subjects , including research on identifiable human material and data ” (World Medical Association, 2013 , 2191, emphasis added). Codes that initially had a narrow focus on medical research have expanded over time to cover new areas, for instance, increasing interest in the storage and use of biospecimens in research (biobanking) led CIOMS to merge its ethical guidelines for epidemiological research and biomedical research in 2016 (CIOMS, xi). Guidelines for research on human subjects are likely to be inclusive about who or what counts as a subject because many of the same ethical issues—privacy and informed consent, for instance—arise whether the subject’s body, tissues, or data are manipulated. In jurisdictions like Canada “human subjects” includes embryos and cadavers, though in the United States (ex vivo) embryos and cadavers are excluded from the definition. This doesn’t necessarily mean the use of cadavers, for instance, is unregulated but rather that it may be regulated differently. In all cases, the potential for harm to an identifiable person raises ethical concern.

If a central focus of research ethics is the prevention or minimization of harm, what then are we to make of the differences between the way humans and nonhuman animals are treated by researchers? The latter are not regarded as human subjects, even on inclusive definitions. And yet the “vast majority of biomedical research activity is conducted on animals or their tissues, cells, or even parts of cells” (Levine 2008 , 214). While research on human subjects is guided by ethical principles such as respect for persons, informed consent, fair subject selection, and a favorable risk–benefit ratio, research on nonhuman animals is typically governed by different approaches, such as the 3R framework: reduction (in numbers of animals used), refinement (improving the conditions for the animals), and replacement (using animals with lower capacity for pain or computer models when possible). Clear demarcation criteria, separating humans from other animals, have been very hard to come by, particularly as researchers discover more about the intellectual, emotional, and social capacities of a wide range of animals from crows to chimpanzees to elephants. The issue of which beings “count” morally, then, is unsettled, and as a result these divisions between the ethical principles applied in each domain rest on unsettled foundations.

It is good to keep this in mind because for many areas of research from neuroscience to immunology animal research is the basis for human research. You can’t typically propose a clinical trial on humans without convincing evidence from animal studies that the intervention might be successful. This expectation persists even though animals are never going to be ideal models for human behaviors, diseases, or functions—the ideal model for humans is humans. The reason why research doesn’t just skip over animals and start with humans, then, is ethical: it is thought to be acceptable to subject animals to risks that we find unacceptable for humans. There are deep and important issues here regarding the relative value of different lives. These issues surface in research ethics when trade-offs are proposed between human and animal studies. For instance, if “higher-level” animals like chimpanzees are no longer used in animal research (for ethical reasons), this may mean that the results from studies on the replacement animals (e.g., mice) lead to more uncertainty in the leap from animal to human studies. But this is at odds with a commitment to reduce harms to human research subjects. It will not be straightforward to find the right ethical path through these trade-offs (for one recent attempt, see Johnson and Barnard 2014 ). But if it is concern about harm to the interests of sentient beings that drives us toward research ethics oversight, we can’t proceed without attending to these difficult decisions. In the discussion of human subjects of research in section 2.1, I reviewed concerns about exploitation that arise when one group is harmed for the benefit of another. If the moral status of animals is even somewhat higher than that of inanimate objects, similar issues will arise when humans extract knowledge for our benefit from the bodies of animals.

In the future, we may have to decide how and whether to proceed with research on advanced forms of artificial intelligence or other nonhuman intelligent beings. So these gaps and unsettled foundations might matter to whether our current divisions between humans and other species are defensible in the long run.

In sum, neither “research” nor “human subjects” is easily defined, and efforts to use these concepts to draw black-and-white ethical lines around activities will struggle with a continuous and growing body of boundary cases. This is a productive realization since it helps us to see the gaps in current regulations (ethical concerns extend far beyond those captured in such regulations) and envision and work toward more efficient and nuanced systems of ethical accountability, such as those aspired to in systems aiming for the deep integration of research and practice (for more on these alternatives, see the chapter by Kim in this handbook). But it is also helpful for those of us working within current systems since it reminds us of the need to keep our focus on what we’re worried about, whether that’s exploitation, disrespect, scientific misconduct, power imbalances within relationships, conflicts of interest, violations of privacy, injustice in the selection of research participants, or opportunity costs when healthcare resources are used inefficiently. And our worries need to be responsive to an ever-changing reality: the internationalization of research, in particular, may well create new incentives (or reinforce existing incentives) that push researchers toward activities that breach different ethical principles or breach well-established principles in new ways. We will always need to be ready to provide timely, creative, and well-grounded responses to new ethical violations.

This chapter aimed to accomplish two things: 1) provide an overview of the scope and practice of research with human subjects and 2) highlight some of the philosophical issues raised by any attempt to provide such an overview. Let us return to our opening cases to see if we can apply what we’ve learned. Using the aim of generalizable knowledge as an initial sorting mechanism, it seems all cases except the family physician who “experiments” with different treatments will qualify as research. This is consistent with most regulatory assessments (keeping in mind they will then exclude and exempt some research from review). And all interventions involve human subjects directly or—in the case of blood samples—indirectly and so would likely be included because identifiable individuals raise ethical concerns about consent and privacy. Embryo research is a tough case, and different jurisdictions and different scholars handle it differently; we didn’t attempt to settle the issue here. Note that while most of the cases turn out to be human subjects research on the most common definitions, we are left with lingering worries—for instance, why does the clinical practice case change from practice to research when it is written up for publication—forget about the regulations, what changes here ethically ? Hopefully it is clear that while some things are settled in this domain, there is still much to work out. As is so often the case in philosophy, even the simplest question—"What is human subjects research?”—is harder to answer than it seems.

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I use the generic term “research ethics committee” in this chapter to refer to the committee providing prospective ethical review of research. In some jurisdictions these have other names, such as “research ethics boards” or “institutional review boards.”

The document goes on to say, “In some cases it can be difficult to make this distinction, underscoring the need to have reviewers or ad hoc advisors . . . who can assist with this determination” (p. 14). This highlights a lesson articulated in this section of the chapter: it is not easy to determine which activities are “research.”

I use the term “boundary cases” here to refer to any study designs that can’t be easily classified as “research” or “practice.” As the examples indicate, this includes “hybrid” or “overlap” activities which intentionally blend research and practice, such as those found in proposed models for learning health care systems.

This is one of the (many) reasons why scholars are so interested in the design and pursuit of learning health care systems in which the research–practice distinction is downplayed or eliminated and new mechanisms of accountability are explored. This and related issues are discussed by Kim elsewhere in this handbook.

The TCPS 2 has a very specific scope: it only covers research funded by the three federal funding agencies in Canada. Other parties, such as independent or private researchers and funders in Canada, typically agree to abide by these rules; but only researchers funded through these agencies are strictly bound by them.

A recent court decision in Newfoundland and Labrador, Canada, for instance, sets this “reasonable” window at 30 days (CBC News 2019 ).

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Scientific Methods and Human Subjects Research

Introduction to Experimental Methods

Karri Haen Whitmer

Our understanding of the methods used to conduct good scientific research is important for progress in our scientific understanding but also impacts our daily lives. Understanding good scientific methodology allows us to not only conduct experiments, but it helps us to analyze research conducted by others. For example, it helps us to determine whether research studies reported in the news are reliable. Research knowledge also helps us to discriminate among different medical treatments when it comes to making personal health decisions.

Scientific research methods include several steps, which may differ depending upon the topic to be addressed by a study. Standard scientific methods typically include: definition of the research problem, conducting background research, formulation of hypotheses, designing and conducting experiments, analysis of results, formulation of conclusions, and communication of research results to the public.

Central to our acquisition of scientific knowledge is the concept of the experiment. Researchers do experiments to answer questions about the world around us. The following are examples of simple research questions in human physiology:

• Does changing the respiratory rate affect heart rate?
• Does caffeine consumption affect blood glucose levels?
• Does body temperature affect blood oxygen levels?

In order to answer these questions, researchers begin by formulating testable hypotheses . A hypothesis is a tentative statement describing the relationship between the variables in an experiment. Research hypotheses are written as if/then statements that include dependent and independent variables.

A variable is any factor that can change, affecting the experimental results. The dependent variable is the variable in the experiment that is measured by the researcher. The independent variable is the variable that is manipulated by the researcher in order to exert an effect on the dependent variable. In the first example research question, the heart rate is the dependent variable, and the respiratory rate is the independent variable. The researcher will use an experimental method (for example deep breathing) to manipulate a subject’s respiratory rate to measure whether any changes occur in the heart rate.

Dependent variable: the variable that is measured as the output of an experiment (the result)

Independent variable: a variable that is manipulated by the researcher

Writing Hypotheses

A hypothesis is a “tentative statement that proposes a possible explanation to some phenomenon or event.” [1]   Hypotheses written for the purpose of conducting experiments must be testable. Formalized hypotheses use an if/then format that helps to assure that all important aspects of the hypothesis are intact, including the independent and dependent variables. Additionally, a good research hypothesis has three parts: an explanation of a phenomenon to be tested, a method, and a prediction. A research hypothesis must be written before an experiment is conducted.

Imagine students working on a physiology project involving muscle contraction and temperature. The students observe that cold hands do not function as well at performing certain tasks requiring manual dexterity than do warm hands. The students decide to test grip strength under different temperature conditions using a handgrip dynamometer, which measures the strength of contraction of hand and forearm muscles.

The following are examples of bad and good research hypotheses for this experiment:

• My grip strength will be stronger with warm hands than with cold hands.

This example is not a research hypothesis because it only includes a prediction. A prediction by itself is never a formalized hypothesis.

• If I test grip strength with a handgrip dynamometer, then my grip strength will be stronger with warm hands than with cold hands.

This example is not a research hypothesis because it only includes a method (a test) and a prediction. It does not include any explanation of the phenomenon to be tested.

• If low temperatures suppress muscle contraction, and I test grip strength at different temperatures with a handgrip dynamometer, then my grip strength will be stronger with warm hands than with cold hands.

This is an example of a correct research hypothesis. Note the three parts: “if low temperatures suppress muscle contraction” (a possible explanation of the phenomenon to be tested), “and I test grip strength at different temperatures with a handgrip dynamometer” (the method used for the test), and “then my grip strength will be stronger with warm hands than with cold hands” (the prediction).

This writing sample is also an example of a formalized hypothesis due to the use of the if/then format. In this hypothesis, the independent variable is muscle temperature, and the dependent variable is muscle contraction strength.

Exercise: Practice writing a research hypothesis

Background: The ad for a creatine supplement claims ingesting 10g of creatine once a day for four weeks results in measurable increases in muscle mass. A student decided to test the claim in 10 subjects by measuring the circumference of the upper arm, around the belly of the biceps muscles, before and after treatment. The subjects were not allowed to take part in weight or resistance training during the testing period.  

Write a hypothesis as an if/then statement for this experiment:

What is the dependent variable?

What is the independent variable?

Designing Experiments involving Humans

Well-designed experiments must minimize the effects of extraneous environmental and physiological factors, in order to make sure changes recorded in the dependent variable are actually the result of manipulating the independent variable. Experimental controls  establish a baseline for the experiment. When conducting human subject experiments in physiology, the control might consist of a separate group of people, the control group , who are not exposed to any manipulation of the independent variable, or it might be the same group of subjects tested before (and then after) altering the independent variable.

Experimental studies may be in vitro , conducted in highly controlled laboratory conditions (example: in a test tube), or in vivo , conducted in a live organism. Controlled laboratory experiments (also called “bench research,” molecular, or cellular research) allow for a great amount of control over the variables that could affect experimental outcomes because all the components in the experimental system can typically be easily accounted for and measured. In human subject research , studies that use human participants to answer a research question, there is typically much less control over experimental variables due to the natural anatomical, physiological, and environmental variation innate to human populations. These are called external variables and can profoundly affect the outcome of an experiment. For example, two subjects may metabolize a compound differently due to differences in enzymes or two subjects that may react to cardiovascular stress differently due to their sex, age, or fitness level. To account for these external, or uncontrolled, variables in human subjects, experiments often use a within-subjects design (below) where the dependent variable is measured in the same subjects before and after manipulating the independent variable.

In human subjects research, there are two main types of experimental designs: within-subjects design and between-subjects design.  In a within-subjects design , the subjects of the study participate under each study condition, including in the control group. In the most simplistic design, the subjects participate in baseline measurements for the control (no treatment) and then participate under experimental conditions. Because the subjects in this kind of study serve as their own control group, variation in the results due to many external variables can be reduced.

An example of a simple within-subjects design can be found in many pharmaceutical studies where a group of participants is given a placebo drug for a defined amount of time, and then the same group is given an experimental drug. Differences in physiological measurements after treatment with the experimental drug are inferred as effects of drug administration.

One disadvantage of this research design is the problem of carryover effects , where the first test adversely influences the other. Two examples of this, with opposite effects, are fatigue and practice. In a complicated experiment, with multiple treatment conditions, the participants may be tired and thoroughly fed up of researchers prying and asking questions and pressuring them into taking tests. This could decrease their performance on the last study. [2]

Alternatively, the practice effect might mean that they are more confident and accomplished after the first condition, simply because the experience has made them more confident about taking tests. As a result, for many experiments, a counterbalance design, where the order of treatments is varied, is preferred, but this is not always possible.

Another type of experimental design is the between-subjects design . In the between-subjects design, there are separate participants for the control and treatment groups, which avoids carryover effects. However, the between-subjects design may make it impossible to maintain homogeneity across the groups: age, gender, and social class are just some of the obvious factors that could result in differences between control and treatment groups, skewing the data.

Within-subjects design: the subjects in the study participate in the control and treatment conditions

Between-subjects design: different groups of subjects participate in the control and treatment conditions

Experimental Error

No matter how careful we are in creating an experimental design, no experiment can be perfect. We must assume there is some margin of error in the collected data. There are three general types of errors that can impact the outcome of an experiment:

• Human error: human errors are simple mistakes made by an experimenter. For example, the experimenter didn’t appropriately attach a sensor or read a patient’s blood pressure wrong.
• Sampling bias: the participants in the study are not representative of the population at large; thus, the results cannot be generalized outside of the study population. For example, data from a study conducted on only 80- year-old men may not be generalized to everyone else in the human population.
• Selection bias: the assignment of subjects to control and treatment groups was not random, resulting in experimental results highly impacted by external variables. For example, a control group that included only females and a treatment group that contained only males.
• Measurement bias: the experimenters rate subjects differently due to their own expectations of experimental outcomes.
• Random error: by-chance variations in measurements that cannot be controlled. Random errors can be reduced by repeated measurements.

The box below lists some sources of error that are possible in all human subject experiments.

Common factors adversely affecting the outcome of human subject experiments:

• Subjects in the study are not representative of the human population at large: e.g., small sample size is too small to fully account for variation in the population
• Interference due to external variables
• Problems with the reliability or accuracy of instruments: e.g., equipment does not have the precision to detect changes in the dependent variable
• Human error: the researcher makes an erroneous measurement or other error

Please cite:

Haen Whitmer, K.M. (2021). A Mixed Course-Based Research Approach to Human Physiology . Ames, IA: Iowa State University Digital Press.  https://iastate.pressbooks.pub/curehumanphysiology/

• http://www.accessexcellence.org/LC/TL/filson/writhypo.html ↵
• Martyn Shuttleworth  (May 16, 2009). Within Subject Design . Retrieved Jul 30, 2019 from Explorable.com:  https://explorable.com/within-subject-design   Creative Commons-License Attribution 4.0 International (CC BY 4.0) . ↵

A Mixed Course-Based Research Approach to Human Physiology Copyright © 2021 by Karri Haen Whitmer is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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How to appropriately choose research subjects

Affiliation.

• 1 Consulting Center of Biomedical Statistics, Academy of Military Medical Sciences, Beijing 100850, China. [email protected]
• PMID: 21419075
• DOI: 10.3736/jcim20110303

The research subject is the first key element of the three key elements in the research design. An appropriate selection of research subjects is crucial to the success of the research. This article summarizes the general principles for the selection of research subjects, the types and numbers of research subjects and the common mistakes that researchers tend to make in the selection of the research subjects. This article also provides the methodology suggestions for the selection of research subjects.

• Patient Selection*
• Research Design*

Module 1: Introduction: What is Research?

Learning Objectives

By the end of this module, you will be able to:

• Explain how the scientific method is used to develop new knowledge
• Describe why it is important to follow a research plan

The Scientific Method consists of observing the world around you and creating a  hypothesis  about relationships in the world. A hypothesis is an informed and educated prediction or explanation about something. Part of the research process involves testing the  hypothesis , and then examining the results of these tests as they relate to both the hypothesis and the world around you. When a researcher forms a hypothesis, this acts like a map through the research study. It tells the researcher which factors are important to study and how they might be related to each other or caused by a  manipulation  that the researcher introduces (e.g. a program, treatment or change in the environment). With this map, the researcher can interpret the information he/she collects and can make sound conclusions about the results.

Research can be done with human beings, animals, plants, other organisms and inorganic matter. When research is done with human beings and animals, it must follow specific rules about the treatment of humans and animals that have been created by the U.S. Federal Government. This ensures that humans and animals are treated with dignity and respect, and that the research causes minimal harm.

No matter what topic is being studied, the value of the research depends on how well it is designed and done. Therefore, one of the most important considerations in doing good research is to follow the design or plan that is developed by an experienced researcher who is called the  Principal Investigator  (PI). The PI is in charge of all aspects of the research and creates what is called a  protocol  (the research plan) that all people doing the research must follow. By doing so, the PI and the public can be sure that the results of the research are real and useful to other scientists.

Module 1: Discussion Questions

• How is a hypothesis like a road map?
• Who is ultimately responsible for the design and conduct of a research study?
• How does following the research protocol contribute to informing public health practices?

Email Updates

Doing Research: A New Researcher’s Guide pp 1–15 Cite as

What Is Research, and Why Do People Do It?

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  
• Open Access
• First Online: 03 December 2022

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Part of the book series: Research in Mathematics Education ((RME))

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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Home » Research Report – Example, Writing Guide and Types

Research Report – Example, Writing Guide and Types

Table of Contents

Research Report

Definition:

Research Report is a written document that presents the results of a research project or study, including the research question, methodology, results, and conclusions, in a clear and objective manner.

The purpose of a research report is to communicate the findings of the research to the intended audience, which could be other researchers, stakeholders, or the general public.

Components of Research Report

Components of Research Report are as follows:

Introduction

The introduction sets the stage for the research report and provides a brief overview of the research question or problem being investigated. It should include a clear statement of the purpose of the study and its significance or relevance to the field of research. It may also provide background information or a literature review to help contextualize the research.

Literature Review

The literature review provides a critical analysis and synthesis of the existing research and scholarship relevant to the research question or problem. It should identify the gaps, inconsistencies, and contradictions in the literature and show how the current study addresses these issues. The literature review also establishes the theoretical framework or conceptual model that guides the research.

Methodology

The methodology section describes the research design, methods, and procedures used to collect and analyze data. It should include information on the sample or participants, data collection instruments, data collection procedures, and data analysis techniques. The methodology should be clear and detailed enough to allow other researchers to replicate the study.

The results section presents the findings of the study in a clear and objective manner. It should provide a detailed description of the data and statistics used to answer the research question or test the hypothesis. Tables, graphs, and figures may be included to help visualize the data and illustrate the key findings.

The discussion section interprets the results of the study and explains their significance or relevance to the research question or problem. It should also compare the current findings with those of previous studies and identify the implications for future research or practice. The discussion should be based on the results presented in the previous section and should avoid speculation or unfounded conclusions.

The conclusion summarizes the key findings of the study and restates the main argument or thesis presented in the introduction. It should also provide a brief overview of the contributions of the study to the field of research and the implications for practice or policy.

The references section lists all the sources cited in the research report, following a specific citation style, such as APA or MLA.

The appendices section includes any additional material, such as data tables, figures, or instruments used in the study, that could not be included in the main text due to space limitations.

Types of Research Report

Types of Research Report are as follows:

Thesis is a type of research report. A thesis is a long-form research document that presents the findings and conclusions of an original research study conducted by a student as part of a graduate or postgraduate program. It is typically written by a student pursuing a higher degree, such as a Master’s or Doctoral degree, although it can also be written by researchers or scholars in other fields.

Research Paper

Research paper is a type of research report. A research paper is a document that presents the results of a research study or investigation. Research papers can be written in a variety of fields, including science, social science, humanities, and business. They typically follow a standard format that includes an introduction, literature review, methodology, results, discussion, and conclusion sections.

Technical Report

A technical report is a detailed report that provides information about a specific technical or scientific problem or project. Technical reports are often used in engineering, science, and other technical fields to document research and development work.

Progress Report

A progress report provides an update on the progress of a research project or program over a specific period of time. Progress reports are typically used to communicate the status of a project to stakeholders, funders, or project managers.

Feasibility Report

A feasibility report assesses the feasibility of a proposed project or plan, providing an analysis of the potential risks, benefits, and costs associated with the project. Feasibility reports are often used in business, engineering, and other fields to determine the viability of a project before it is undertaken.

Field Report

A field report documents observations and findings from fieldwork, which is research conducted in the natural environment or setting. Field reports are often used in anthropology, ecology, and other social and natural sciences.

Experimental Report

An experimental report documents the results of a scientific experiment, including the hypothesis, methods, results, and conclusions. Experimental reports are often used in biology, chemistry, and other sciences to communicate the results of laboratory experiments.

Case Study Report

A case study report provides an in-depth analysis of a specific case or situation, often used in psychology, social work, and other fields to document and understand complex cases or phenomena.

Literature Review Report

A literature review report synthesizes and summarizes existing research on a specific topic, providing an overview of the current state of knowledge on the subject. Literature review reports are often used in social sciences, education, and other fields to identify gaps in the literature and guide future research.

Research Report Example

Following is a Research Report Example sample for Students:

Title: The Impact of Social Media on Academic Performance among High School Students

This study aims to investigate the relationship between social media use and academic performance among high school students. The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The findings indicate that there is a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students. The results of this study have important implications for educators, parents, and policymakers, as they highlight the need for strategies that can help students balance their social media use and academic responsibilities.

Introduction:

Social media has become an integral part of the lives of high school students. With the widespread use of social media platforms such as Facebook, Twitter, Instagram, and Snapchat, students can connect with friends, share photos and videos, and engage in discussions on a range of topics. While social media offers many benefits, concerns have been raised about its impact on academic performance. Many studies have found a negative correlation between social media use and academic performance among high school students (Kirschner & Karpinski, 2010; Paul, Baker, & Cochran, 2012).

Given the growing importance of social media in the lives of high school students, it is important to investigate its impact on academic performance. This study aims to address this gap by examining the relationship between social media use and academic performance among high school students.

Methodology:

The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The questionnaire was developed based on previous studies and was designed to measure the frequency and duration of social media use, as well as academic performance.

The participants were selected using a convenience sampling technique, and the survey questionnaire was distributed in the classroom during regular school hours. The data collected were analyzed using descriptive statistics and correlation analysis.

The findings indicate that the majority of high school students use social media platforms on a daily basis, with Facebook being the most popular platform. The results also show a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students.

Discussion:

The results of this study have important implications for educators, parents, and policymakers. The negative correlation between social media use and academic performance suggests that strategies should be put in place to help students balance their social media use and academic responsibilities. For example, educators could incorporate social media into their teaching strategies to engage students and enhance learning. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. Policymakers could develop guidelines and policies to regulate social media use among high school students.

Conclusion:

In conclusion, this study provides evidence of the negative impact of social media on academic performance among high school students. The findings highlight the need for strategies that can help students balance their social media use and academic responsibilities. Further research is needed to explore the specific mechanisms by which social media use affects academic performance and to develop effective strategies for addressing this issue.

Limitations:

One limitation of this study is the use of convenience sampling, which limits the generalizability of the findings to other populations. Future studies should use random sampling techniques to increase the representativeness of the sample. Another limitation is the use of self-reported measures, which may be subject to social desirability bias. Future studies could use objective measures of social media use and academic performance, such as tracking software and school records.

Implications:

The findings of this study have important implications for educators, parents, and policymakers. Educators could incorporate social media into their teaching strategies to engage students and enhance learning. For example, teachers could use social media platforms to share relevant educational resources and facilitate online discussions. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. They could also engage in open communication with their children to understand their social media use and its impact on their academic performance. Policymakers could develop guidelines and policies to regulate social media use among high school students. For example, schools could implement social media policies that restrict access during class time and encourage responsible use.

References:

• Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237-1245.
• Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Journal of the Research Center for Educational Technology, 8(1), 1-19.
• Pantic, I. (2014). Online social networking and mental health. Cyberpsychology, Behavior, and Social Networking, 17(10), 652-657.
• Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948-958.

Note*: Above mention, Example is just a sample for the students’ guide. Do not directly copy and paste as your College or University assignment. Kindly do some research and Write your own.

Applications of Research Report

Research reports have many applications, including:

• Communicating research findings: The primary application of a research report is to communicate the results of a study to other researchers, stakeholders, or the general public. The report serves as a way to share new knowledge, insights, and discoveries with others in the field.
• Informing policy and practice : Research reports can inform policy and practice by providing evidence-based recommendations for decision-makers. For example, a research report on the effectiveness of a new drug could inform regulatory agencies in their decision-making process.
• Supporting further research: Research reports can provide a foundation for further research in a particular area. Other researchers may use the findings and methodology of a report to develop new research questions or to build on existing research.
• Evaluating programs and interventions : Research reports can be used to evaluate the effectiveness of programs and interventions in achieving their intended outcomes. For example, a research report on a new educational program could provide evidence of its impact on student performance.
• Demonstrating impact : Research reports can be used to demonstrate the impact of research funding or to evaluate the success of research projects. By presenting the findings and outcomes of a study, research reports can show the value of research to funders and stakeholders.
• Enhancing professional development : Research reports can be used to enhance professional development by providing a source of information and learning for researchers and practitioners in a particular field. For example, a research report on a new teaching methodology could provide insights and ideas for educators to incorporate into their own practice.

How to write Research Report

Here are some steps you can follow to write a research report:

• Identify the research question: The first step in writing a research report is to identify your research question. This will help you focus your research and organize your findings.
• Conduct research : Once you have identified your research question, you will need to conduct research to gather relevant data and information. This can involve conducting experiments, reviewing literature, or analyzing data.
• Organize your findings: Once you have gathered all of your data, you will need to organize your findings in a way that is clear and understandable. This can involve creating tables, graphs, or charts to illustrate your results.
• Write the report: Once you have organized your findings, you can begin writing the report. Start with an introduction that provides background information and explains the purpose of your research. Next, provide a detailed description of your research methods and findings. Finally, summarize your results and draw conclusions based on your findings.
• Proofread and edit: After you have written your report, be sure to proofread and edit it carefully. Check for grammar and spelling errors, and make sure that your report is well-organized and easy to read.
• Include a reference list: Be sure to include a list of references that you used in your research. This will give credit to your sources and allow readers to further explore the topic if they choose.
• Format your report: Finally, format your report according to the guidelines provided by your instructor or organization. This may include formatting requirements for headings, margins, fonts, and spacing.

Purpose of Research Report

The purpose of a research report is to communicate the results of a research study to a specific audience, such as peers in the same field, stakeholders, or the general public. The report provides a detailed description of the research methods, findings, and conclusions.

Some common purposes of a research report include:

• Sharing knowledge: A research report allows researchers to share their findings and knowledge with others in their field. This helps to advance the field and improve the understanding of a particular topic.
• Identifying trends: A research report can identify trends and patterns in data, which can help guide future research and inform decision-making.
• Addressing problems: A research report can provide insights into problems or issues and suggest solutions or recommendations for addressing them.
• Evaluating programs or interventions : A research report can evaluate the effectiveness of programs or interventions, which can inform decision-making about whether to continue, modify, or discontinue them.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies.

When to Write Research Report

A research report should be written after completing the research study. This includes collecting data, analyzing the results, and drawing conclusions based on the findings. Once the research is complete, the report should be written in a timely manner while the information is still fresh in the researcher’s mind.

In academic settings, research reports are often required as part of coursework or as part of a thesis or dissertation. In this case, the report should be written according to the guidelines provided by the instructor or institution.

In other settings, such as in industry or government, research reports may be required to inform decision-making or to comply with regulatory requirements. In these cases, the report should be written as soon as possible after the research is completed in order to inform decision-making in a timely manner.

Overall, the timing of when to write a research report depends on the purpose of the research, the expectations of the audience, and any regulatory requirements that need to be met. However, it is important to complete the report in a timely manner while the information is still fresh in the researcher’s mind.

Characteristics of Research Report

There are several characteristics of a research report that distinguish it from other types of writing. These characteristics include:

• Objective: A research report should be written in an objective and unbiased manner. It should present the facts and findings of the research study without any personal opinions or biases.
• Systematic: A research report should be written in a systematic manner. It should follow a clear and logical structure, and the information should be presented in a way that is easy to understand and follow.
• Detailed: A research report should be detailed and comprehensive. It should provide a thorough description of the research methods, results, and conclusions.
• Accurate : A research report should be accurate and based on sound research methods. The findings and conclusions should be supported by data and evidence.
• Organized: A research report should be well-organized. It should include headings and subheadings to help the reader navigate the report and understand the main points.
• Clear and concise: A research report should be written in clear and concise language. The information should be presented in a way that is easy to understand, and unnecessary jargon should be avoided.
• Citations and references: A research report should include citations and references to support the findings and conclusions. This helps to give credit to other researchers and to provide readers with the opportunity to further explore the topic.

Advantages of Research Report

Research reports have several advantages, including:

• Communicating research findings: Research reports allow researchers to communicate their findings to a wider audience, including other researchers, stakeholders, and the general public. This helps to disseminate knowledge and advance the understanding of a particular topic.
• Providing evidence for decision-making : Research reports can provide evidence to inform decision-making, such as in the case of policy-making, program planning, or product development. The findings and conclusions can help guide decisions and improve outcomes.
• Supporting further research: Research reports can provide a foundation for further research on a particular topic. Other researchers can build on the findings and conclusions of the report, which can lead to further discoveries and advancements in the field.
• Demonstrating expertise: Research reports can demonstrate the expertise of the researchers and their ability to conduct rigorous and high-quality research. This can be important for securing funding, promotions, and other professional opportunities.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies. Producing a high-quality research report can help ensure compliance with these requirements.

Limitations of Research Report

Despite their advantages, research reports also have some limitations, including:

• Time-consuming: Conducting research and writing a report can be a time-consuming process, particularly for large-scale studies. This can limit the frequency and speed of producing research reports.
• Expensive: Conducting research and producing a report can be expensive, particularly for studies that require specialized equipment, personnel, or data. This can limit the scope and feasibility of some research studies.
• Limited generalizability: Research studies often focus on a specific population or context, which can limit the generalizability of the findings to other populations or contexts.
• Potential bias : Researchers may have biases or conflicts of interest that can influence the findings and conclusions of the research study. Additionally, participants may also have biases or may not be representative of the larger population, which can limit the validity and reliability of the findings.
• Accessibility: Research reports may be written in technical or academic language, which can limit their accessibility to a wider audience. Additionally, some research may be behind paywalls or require specialized access, which can limit the ability of others to read and use the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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IRB Application Guide

All new human subjects research must be reviewed by the IRB prior to the commencement of any study activity. The IRB Application Guide will assist UT Austin faculty, staff and students who are planning to conduct research involving human subjects.

Once IRB approval or determination has been granted, researchers must follow IRB Policies and Procedures for follow-on submissions during the course of their research study to remain in compliance. Examples of follow-on submissions include modifications, continuing reviews (when applicable), and reportable new information reports.

Forms, templates and guidance documents are available for download via the UTRMS-IRB Library.

How to Submit an Initial IRB Application (New Study)

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Download templates from the UTRMS-IRB Library Templates page. One of the following must accompany an online submission.

HRP-UT901 – Template IRB Proposal Standard Submission

Use of greater than minimal risk studies and minimal risk studies that fit into one or more expedited categories (see Section 5.3 of the IRB Policies and Procedures Manual for details regarding expedited research). Do NOT submit this form if the study will qualify for exempt review (see Section 5.4 of the IRB Policies and Procedures Manual for details regarding exempt research).

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Use for studies that are ONLY utilizing secondary data or specimens and that meet the criteria for human subjects research. If conducting chart reviews only (retrospective or prospective) use this form; do not use the exempt form or standard submission form.

HRP-UT912 – Template IRB Proposal Humanitarian Use Device Submission

Use this form ONLY for HUD submissions.

Download applicable form from the UTRMS-IRB Library Templates page.

If the research involves any of the following, submit the appropriate Supplemental form with the UTRMS-IRB application: biospecimens (HRP-UT904), investigational device (HRP-UT905), investigational drug/biologic (HRP-UT906), PHI (HRP-UT907), international research (HRP-UT908), prisoners (HRP-UT909), registry/repository (HRP-UT910), Department of Defense (DoD) sponsored/funded (HRP-UT911).

The UT IRB has consent, parental permission and assent form templates available for download in UTRMS-IRB Library Templates. English and Spanish versions of the templates are currently available. It is recommended that researchers use the available templates for a more efficient review.

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Applying for Modifications

Changes in study procedure or personnel for studies that were reviewed and approved as expedited or full board must be submitted and approved by the IRB prior to implementation by submitting a modification application in UTRMS-IRB. By starting a modification application, the currently approved IRB application is opened for editing. This allows researchers to alter, delete or add to the current application and/or supplemental documents.

Exceptions to this process can only be made when there are concerns for subject safety. If there are subject safety concerns, email [email protected] as soon as possible. as soon as possible. See Section 8: Modification/Amendment of Human Subjects Research Activities in UT IRB Policies and Procedures for additional information.

Studies determined to be exempt at time of initial review require a modification submitted via UTRMS-IRB if the change(s) to the research involve a change in PI, increase risk to participants or otherwise affect the exempt category or the criteria for exempt determination. Researchers are encouraged to contact IRB staff if unsure whether proposed changes to exempt research would require a modification application.

To submit a modification application, log in to UTRMS-IRB, and navigate to the study to modify. Under Next Steps, click “Create Modification/CR/Closure” and select “Modification/Update.”

• If ONLY changing research personnel, choose “Study team member information” as the modification scope. For all other changes, choose “Other parts of the study”.

Complete the Modification application by summarizing the modifications such that IRB reviewers can adequately understand proposed changes. Use the “Update” button to upload revised versions of currently approved study documents. To add brand new study documents, click the “+Add” button to upload.

Continuing Review

Annual continuing reviews are required for greater than minimal risk research, research regulated by the FDA and research sponsored/funded by the Department of Justice. Most minimal risk research studies approved via the expedited review pathway do not require annual continuing review. The IRB may require continuing review for special circumstances, to be determined on a study-by-study basis and documented as part of the review.

Researchers can identify if their study requires a continuing review by confirming if there is an approval end date present on the study workspace. UTRMS-IRB will also send periodic reminders to notify researchers if their study requires a continuing review.

To submit a continuing review application, log into UTRMS-IRB and navigate to the study to modify. Under Next Steps, click “Create Modification/CR/Closure” and select “Continuing Review/Study Closure”. Complete the continuing review application.

To submit a modification along with a continuing review, choose “Modification/Continuing Review” and complete the application.

Reportable New Information (RNI)

To ensure the protection of research participants, the IRB requires investigators to report certain information during the course of the research, either promptly or at the time of continuing review. This may include events where participants experience unanticipated problems or when there is potential noncompliance.

For the IRB policy regarding reporting unanticipated problems or instances of potential noncompliance, see Section 9: Reporting Unanticipated Problems and Section 22: Protocol Deviations and Noncompliance of the IRB Policies and Procedures Manual .

Written reports from study monitors, including Data Safety and Monitoring Board reports can be uploaded for IRB review via the RNI process.

To submit an RNI, log into UTRMS-IRB and click on “Report New Information”. Complete the RNI SmartForm. When describing the information, include the following as applicable:

• What happened, when and where
• What factors and contributed (role, not name) to why it happened
• What was done to address the issue before submitting the RNI to the IRB
• What is the plan going forward for preventing this from happening again
• If “yes” is answered to any of these questions, include additional details as applicable in the description section.
• If the event is related to a current study (or studies), choose the related study in question 8.
• If the event is for a study where UT Austin deferred IRB review to an external IRB, upload the reviewing IRB’s determination letter. If not available at the time of submission, proceed with submission and upload once available.
• Click Continue when you have completed the application and Submit to submit the application for review.

The RNI will undergo initial pre-review by IRB staff to ensure that the submission is complete and in keeping with the IRB requirements. The RNI submitter may be asked to provide additional information. Once the submission is determined to be complete and if the RNI requires further IRB review, it will be routed for expedited or full board review as appropriate.

If during review, the event reported clearly does not meet the criteria for an unanticipated problem or potential noncompliance, the IRB staff may acknowledge the report.

Expedited Review

The submission is sent to an IRB member for review. The submission will receive one of the following determinations:

• Non-compliance that is neither serious nor continuing
• None of the above (not noncompliance, not an unanticipated problem, etc.)

An acknowledgement letter that may or may not request additional actions will be issued via UTRMS-IRB. If additional action is specified, a modification or additional RNI must be submitted, as applicable.

Full Board Review

The submission will be assigned to a Board meeting for review. The submission will be presented at a convened meeting for discussion. The submission will receive at least one of the following determinations by the IRB:

• Unanticipated problem involving risks to subjects or others
• Serious non-compliance
• Continuing non-compliance
• Suspension or termination of IRB approval
• None of the above

If the IRB determines the reported event constituted an unanticipated problem or serious and/or continuing noncompliance and the study is funded by HHS or subject to FDA regulations, these agencies will be notified by the IRB of this finding.

An acknowledgement letter that may or may not request additional actions will be issued via UTRMS-IRB. If additional action is specified, a modification or an additional RNI must be submitted, as applicable.

Study Closure

A closure report must be submitted to the IRB in UTRMS-IRB for each human research study, regardless of whether a study is subject to continuing review requirement. Investigators are required to submit final study closure reports when all of the following apply:

• Study is permanently closed to enrollment,
• Participants have completed all research activities, and
• Collection and analysis of identifiable information is complete.

To submit a closure application, log into UTRMS-IRB and navigate to the relevant study. Under Next Steps, click “Create Modification/CR/Closure” and select “Continuing Review/Study Closure”. Complete the Continuing Review/Closure application.

Email Notices

The Office of Research Support and Compliance and Compliance notifies PIs 90, 60 and 30 days prior to the study expiration date. These emails are automated and only warnings about the upcoming expiration date. All emails are sent to the email address on file in Workday.

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ENLS 101: Law and Literature : Literature Resources

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All of Us - National Institutes of Health (NIH)

UIC's Role in All of Us

In Illinois, many participants are joining the All of Us program through the Illinois Precision Medicine Consortium, which includes the University of Illinois at Chicago and UI Health, the university’s academic medical center and clinics, as well as Northwestern University, the University of Chicago, Rush University Medical Center, NorthShore University Health System, and other affiliates such as Cook County Hospital, UIC College of Medicine in Peoria, Erie Family Health Centers and NorthShore Health Centers to use the data to develop precision preventive strategies and treatments for both rare conditions and common acute and chronic diseases that may affect diverse populations differently.

If you have questions or want to learn more, contact a librarian here.   

What is All of Us

The National Institutes of Health’s (NIH’s) All of Us Research Program is building one of the largest biomedical data resources of its kind with health data from a diverse group of participants across the United States, including people and communities who have been left out of medical research in the past. Data include biological factors and social determinants of health on a large, inclusive scale that tracks participants as they move, age, and grow (longitudinal study design).  

Data sources include: 

Electronic Health Records (EHR) standardized using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) 

Biosamples and bioassays from blood, saliva, and/or urine samples 

Survey responses on identities and backgrounds, overall health, lifestyles, medical histories, healthcare access, experiences with COVID-19, and more 

Physical measurements when joining program 

Heart rate, physical activity, and sleep as tracked by wearable devices

The diverse database, which is a part of the Precision Medicine Initiative , is intended to inform studies on a multitude of heath conditions.

What is Precision Medicine

Precision medicine is individualized care that considers the environment, lifestyle, family health history, and genetic makeup of a patient. It acknowledges that certain treatments work differently for people with different backgrounds, treats patients as individuals, and can reduce health care costs by providing the right treatment the first time. Learn more about precision medicine in:

The Goal of All of Us

The goal of  All of Us  is to speed up health research discoveries, enabling new kinds of individualized health care. To make this possible, the program is building one of the world’s largest and most diverse databases for health research.

By working with participants across the country, collecting many types of information over time, and building a data platform that many researchers can use,  All of Us  may also shape how people do research in the future.

Core Values

The  All of Us  Research Program is guided by a set of core values:

• Participation is open to all.  People of every race, ethnicity, sex, gender, and sexual orientation are welcome.   
• Participants reflect the rich  diversity  of the United States.  To develop individualized plans for disease prevention and treatment, researchers need more data about the differences that make each of us unique. Having a diverse group of participants can lead to important breakthroughs.   
• Participants are  partners .  Participants shape the program with their input and contribute to a project that may improve the health of future generations. They may also learn about their own health.   
• Transparency earns trust.  We inform participants about how their data are used, accessed, and shared. Participants can choose how much information to share.  
• Participants have access to their information.  All of Us  lets participants see their own information and records.  
• Data are broadly accessible for research purposes.  All of Us  makes information about participants as a group available in a  public database . Everyone can explore the database or use it to make discoveries. Data from individual participants are also available, but only for researchers who apply and are approved. Any personal information that identifies a participant, such as name or address, is removed from data that researchers can access.  
• Security and privacy are of highest importance.  Data are stored in a secure, cloud-based database. All systems meet the requirements of the Federal Information Security Management Act. Ongoing security tests help protect participant data. Learn more about how the  All of Us  Research Program  protects data and privacy .

All of Us centers. . .

• Breadth.  With a goal of enrolling one million or more participants in the United States,  All of Us  is building one of the largest health databases of its kind. As the amount of data grows, patterns will emerge that wouldn’t be visible at a smaller scale.  
• Diversity.  The program is enrolling a large group of people that reflects the  diversity  of the United States. This includes people who haven’t taken part in or have been left out of health research before.  All of Us  welcomes participants of all backgrounds and walks of life, from all regions of the country, whether they are healthy or sick.  
• Depth.   All of Us  collects many types of data, including data from surveys, electronic health records, and blood and urine tests. Over time, participants may share data in new ways, using wearable fitness trackers and other technologies.   
• Duration.  The initial plan for the program spans 10 years, but it may last even longer. Working with participants over the long term means the program can gather more information that will help researchers find out how health and disease change over time.  
• Innovation.   All of Us  is working to take research to a new level. The program is working with participants across the country, collecting many types of information over time, and building a  database  that many researchers can use. This new model could shape how people do research in the future.  
• Access.   All of Us  aims to make it easy for a variety of researchers—from university professors to citizen scientists—to make discoveries using the program’s data. Multiple systems and processes keep data secure and participants’ personal information private.  
• Engagement.   Participants are partners  in  All of Us.  Participant input is welcome on every aspect of the program to make it better. Participants will have full access to data they share and information about all research projects that use  All of Us  data.
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Great white shark trackers: OCEARCH expedition to follow sharks' transition north from Florida

Great white sharks spend winters down south, including the warm waters around Florida, and as they head back north this spring scientists will be there to study them.

OCEARCH , a non-profit research group studying the ocean's giants, will launch its 47th ocean expedition , dubbed Expedition Northbound II, aboard the M/V OCEARCH, from Jacksonville , Florida on April 1.

According to the group's expedition page , the study's goal is to learn more about how the animals use their overwintering area and their reproductive readiness as they end their overwintering period and head up north.

"We're excited to be back out on the water next week to embark on Expedition Northbound II to collect data for our Western North Atlantic White Shark Study," the group posted on X Sunday.

Over the past 10 years, OCEARCH has tagged and collected data on nearly 100 North Atlantic white sharks amid its mission to "solve the Global White Shark Puzzle," the group's website notes. This group of sharks has a range spanning Atlantic Canada, the U.S. East Coast and the Gulf of Mexico.

The sharks are outfitted with satellite tags attached to their dorsal fins, allowing scientists to track their locations as the tags break the water's surface and transmit location information via pings. The sharks' travels can be viewed on the OCEARCH shark tracker map.

The three-week expedition is expected to end April 21 in Charleston, South Carolina.

What is OCEARCH?

OCEARCH is a nonprofit research organization studying the ocean's giants.

The group studies great white sharks and other keystone species essential for the health of the oceans.

OCEARCH is launching its 47th expedition on April 1. It departs from Jacksonville, Florida and is scheduled to make its final docking in Charleston, South Carolina on April 21.

During expeditions, researchers have collected previously unattainable data on the animals' migrations, reproductive cycle, genetic status, diet, abundance, and more.

"If we lose the apex predator (sharks) then we lose all our fish and then there are no fish sandwiches for our grandchildren," OCEARCH founder Chris Fischer told the  Courier Journal . "That's oversimplified, of course, but the idea is important because many shark species are threatened by overfishing and a demand for shark fins in Asia. Their dwindling numbers jeopardize ocean habitats."

What is the OCEARCH shark tracker? One shark 'drew' shark portrait

OCEARCH provides an online map tracking the tagged shark's travels.

Each animal has a Smart Position and Temperature Transmitting Tag (SPOT) tag attached to its dorsal fin which emits a ping when it breaks the water's surface for a short time and transmits location information to trackers.

The most notable tracker page belongs to a 13-foot 3-inch white shark nicknamed Breton . The 1,437-pound shark's pings from September 2020 to January 2022 connect to show what appears to be the outline of a colossal shark, with the tail in Nova Scotia, the body spanning the East Coast and the head pointing at Florida's east coast.

How many sharks has OCEARCH tagged?

According to its tracker, OCEARCH has tagged 371 sharks, including 123 great white sharks.

• 123 great white sharks
• 144 tiger sharks
• 9 blacktip sharks
• 29 shortfin mako sharks
• 25 blue sharks
• 18 hammerhead sharks
• 6 silky sharks
• 6 bull sharks
• 8 whale sharks
• 3 great hammerhead sharks

The group has also tagged alligators, dolphins, seals, swordfish and turtles.

Great white shark facts

Here are some things to know about white sharks, according to  NOAA Fisheries :

• White sharks grow slowly. Males mature at around 26 years old and females at around 33 years old. Life expectancy is difficult to determine but is estimated to be between 30 and 70 years.
• White sharks are about 4 feet long at birth but can grow up to about 20 feet long and weigh over 4,000 pounds.
• White sharks eat an opportunistic diet of fish, invertebrates and marine mammals.
• White sharks are partially warm-blooded and can maintain their internal body temperature above that of the surrounding water. This allows them to be more active in cooler waters than cold-blooded species.

Great white sharks in Florida?

Great white  sharks  migrate south when the water gets cold and food sources become scarce up north, according to  OCEARCH chief scientist Dr. Bob Hueter .

Think of them as the snowbirds of sharks.

Most of them tend to stay away from the beaches in continental shelf waters, Hueter said.

Most shark attacks happen in Florida

There were 69 documented unprovoked  shark attacks  around the globe in 2023. The U.S. led the world with 36 attacks and Florida again was the state with the most bites at 16.

Florida shark attacks by county:

• Volusia County:  8
• Brevard County : 2
• St. Lucie County : 2
• Miami-Dade County: 1
• Palm Beach County : 1
• Escambia County : 1
• Pinellas County: 1

While the U.S. has the most attacks, South Africa has the most shark-related fatalities.

In the past 47 years, there have been  1,230 shark bites  worldwide, according to data from  floridapanhandle.com , with  great white sharks credited as the top biters . No white shark has been identified in a Florida shark bite from 1926 to present, according to Shark Attack File .

Support local journalism by  subscribing to a Florida news organization .

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How to obtain informed consent for research

1 University of Messina, “G. Martino” Hospital, Messina, Italy

Amelia Licari

2 University of Pavia, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

Current biomedical research on human subjects requires clinical trial, which is defined as “any research study that prospectively assigns human participants or groups of humans to one or more health-related interventions [ i.e. drugs, cells or other biological products, surgical procedures, devices] to evaluate the effects on health outcomes” [1]. In our modern ethical conception, all research conducted on humans must be pre-emptively accepted by the subjects themselves through the procedure known as informed consent, which is a process by which “a subject voluntarily confirms his or her willingness to participate in a particular trial, after having been informed of all aspects of the trial that are relevant to the subject’s decision to participate”, as stated in the International Council for Harmonisation Good Clinical Practice guidelines [2]. Informed consent is documented by means of a written, signed and dated informed consent form. This form is required in the following cases: 1) when the research involves patients, children, incompetent/incapacitated persons, healthy volunteers, immigrants or others ( e.g. prisoners); 2) when the research uses/collects human genetic material, biological samples or personal data [3].

Short abstract

The process of obtaining informed consent for clinical trials is tightly regulated; complications arise in circumstances when consent may be waived, or when needed from vulnerable populations http://ow.ly/rEMe30j5MVq

Current biomedical research on human subjects requires clinical trial, which is defined as “any research study that prospectively assigns human participants or groups of humans to one or more health-related interventions [ i.e. drugs, cells or other biological products, surgical procedures, devices] to evaluate the effects on health outcomes” [ 1 ]. In our modern ethical conception, all research conducted on humans must be pre-emptively accepted by the subjects themselves through the procedure known as informed consent, which is a process by which “a subject voluntarily confirms his or her willingness to participate in a particular trial, after having been informed of all aspects of the trial that are relevant to the subject’s decision to participate”, as stated in the International Council for Harmonisation Good Clinical Practice guidelines [ 2 ]. Informed consent is documented by means of a written, signed and dated informed consent form. This form is required in the following cases: 1) when the research involves patients, children, incompetent/incapacitated persons, healthy volunteers, immigrants or others ( e.g. prisoners); 2) when the research uses/collects human genetic material, biological samples or personal data [ 3 ].

The informed consent form must be written in language easily understood by the subjects, it must minimise the possibility of coercion or undue influence, and the subject must be given sufficient time to consider participation. However, informed consent is not merely a form that is signed, but is a process in which the subject has an understanding of the research and its risks, and it is tightly described in ethical codes and regulations for human subject research [ 2 ].

Educational aims

• To provide a comprehensive overview of issues in obtaining informed consent in clinical research.
• To describe the process of obtaining informed consent in clinical trials.
• To highlight the circumstances under which informed consent can be waived.
• To review the setting of obtaining informed consent from “vulnerable populations”.

The informed consent process

The voluntary expression of the consent by a competent subject and the adequate information disclosure about the research are critical and essential elements of the informed consent process [ 4 ]. Competent subjects able to comprehend the research-related information should personally decide and provide the consent on research participation. Conditions posing practical challenges in obtaining informed consent from the real subject may include situations of medical emergency or obtaining consent from “vulnerable” subjects and/or children [ 5 ].

Research-related information must be presented to enable people to voluntarily decide whether or not to participate as a research subject. For an ethically valid consent, information provided to a research subject should include, but not be limited to: information about the health condition for which the research is proposed; details of the nature and purpose of the research; the expected duration of the subject’s participation; a detailed description of study treatment or intervention and of any experimental procedures (including, in the case of randomised clinical trials (RCTs), also blinding and randomisation); a statement that participation in research is voluntary; probable risks and benefits associated with research participation; details of the nature of the illness and possible outcome if the condition is left untreated; availability, risks and benefits of alternative treatments; information about procedures adopted for ensuring data protection/confidentiality/privacy, including duration of storage of personal data; details about the handling of any incidental findings of the research; description of any planned genetic tests; details of insurance coverage in case of injury; reference contacts for any further answers to pertinent questions about the research and the subject’s rights and in case of any research-related injury to the subject; and any other information that seems necessary for an informed decision to be taken by the subject. Of particular importance, a statement offering the subject the opportunity to withdraw at any time from the research without consequences must be provided during the information disclosure [ 2 ]. Specific information should be provided in case of research projects involving children, incapacitated adults not able to give informed consent, illiterate populations, etc. (as will be described later in this article).

The information about the research should be given by a physician or by other individuals ( i.e.  researchers) with appropriate scientific training and qualifications [ 6 ]. Furthermore, the location where the informed consent is being discussed, and the subject’s physical, emotional and psychological capability, must be taken into consideration when taking consent from a human subject.

Informed consent: when is it not necessary?

After institutional review board (IRB) or independent ethics committee approval is achieved, obtaining informed consent from each human subject prior to his/her participation in clinical trial is mandatory [ 5 ]. However, when specific circumstances occur, the informed consent can be waived, and “research without consent” is possible, which allows enrolment of patients without their consent, under strict regulation [ 7 ]. In order that research without consent is considered justifiable, the following three conditions have to be met: 1) it is impracticable to obtain consent, 2) the research does not infringe the principle of self-determination, and 3) the research provides significant clinical relevance [ 8 ].

The first condition, of “impracticability”, occurs when obtaining informed consent is burdened by high impact in terms of time and economic resources or could compromise the study’s validity [ 8 ]. The second condition means that, although physicians are requested to ensure that the patient has understood the aim of the research and the risks and/or benefits associated with study participation, the researchers are also advised to respect the patient’s decision-making capacity, not interfering with his/her decisions and acting always in the patient’s best interest [ 9 ]. The third condition leads to justification of waiving consent when the clinical relevance and public health importance are potentially high [ 8 ].

The formal literature identifies different types of RCTs and classifies them into three macro-areas: 1) RCTs based on infeasibility of informed consent; 2) RCTs that omit informed consent only for control groups; and 3) RCTs that omit informed consent entirely.

RCTs based on infeasibility of informed consent

Emergency clinical studies, involving critically ill subjects, represent an exception to the requirement of informed consent. The investigated life-saving therapy and the medical intervention may be required immediately, not permitting the researchers to wait and respect all procedures of obtaining informed consent. Within this context, the researchers will be able to proceed with patient recruitment, also without the subject’s consent to treatment, when, prior to the study, the IRB has ascertained the presence of mandatory conditions ( table 1 ) [ 10 ].

Table 1

Conditions to be met in emergency clinical study

Cluster randomised studies include cluster-cluster and individual-cluster research [ 11 ]. In cluster-cluster designs ( e.g. studies on infectious disease prevention), the intervention involves the entire target community, so that single subjects cannot refuse it [ 12 ]. Conversely, in individual-cluster designs ( e.g. studies on primary care), although the intervention involves all the selected community, the right to refuse treatment is allowed. Under this circumstance, the omission of informed consent is justified only when the treatment refusal undermines the validity of the research study and/or procedures [ 13 ].

RCTs that omit informed consent only for control groups

In Zelen’s single-consent model ( e.g. RCTs in infectious or oncological diseases), randomisation occurs prior to any consent, and informed consent is sought only from individuals assigned to experimental treatment [ 14 ]. In the control group, the physicians do not make substantial changes in routine patient care, so informed consent is not required for patient enrolment [ 8 ].

In order to improve study recruitment, Zelen developed the double-consent design. Specifically, informed consent is requested for subjects to be involved in the study but not for the randomisation, preventing psychological distress [ 14 ].

In follow-up studies, the nested consent model ( e.g. for single cohort studies) or cohort multiple RCTs model ( e.g. for multiple cohort studies) is applied. In these variants, patients give their consent for prospective follow-up; however, they remain blinded to any randomised experimental interventions [ 15 ].

In trials using the model of “consent to postponed information”, the informed consent process is carried out after the study is completed [ 16 ].

All these RCT types aim to avoid unnecessary stress in patients who will not receive the new promising experimental treatment. Moreover, these clinical study designs do not affect the standard therapeutic approach or infringe the rights of the patients in the control group; therefore, the clinical trial can proceed without obtaining informed consent [ 8 ].

RCTs that omit informed consent entirely

Based on the fact that patients are assigned to standard care interventions, no informed consent is sought either in low-risk pragmatic RCTs [ 17 ] or in prompted optional randomisation trials [ 18 , 19 ]. However, in a low-risk pragmatic RCT, patients do not have the possibility to choose one of the two standard treatments, whereas in a prompted optional randomisation trial, both the researchers and the enrolled patients can choose one type of treatment over another, despite the randomisation results [ 6 ].

Special needs: vulnerable patients

A “vulnerable population” is defined as a disadvantaged community subgroup unable to make informed choices, protect themselves from inherent or intended risks, or keep their own interests safeguarded [ 20 ]. In the health domain, “vulnerable populations” refers to physical vulnerability ( e.g. pregnant women, fetuses, children, orphans, students, employees, prisoners, the military, and those who are chronically or terminally ill), psychological vulnerability (cognitively and intellectually impaired individuals) and social vulnerability (those who are homeless, from ethnic minorities, are immigrants or refugees) [ 20 ].

Due to a compromised free will and inability to make conscious decisions, several ethical dilemmas (related to communications, privacy and treatment) often arise when research involves these populations. Guaranteeing protection of rights, safety, data privacy and confidentiality of vulnerable subjects are prerogatives of good clinical practice, and law dispositions are regulated and strictly monitored by the applicable authorities [ 21 ].

Physical vulnerability

For a long time, pregnant women were excluded from clinical research because of their “vulnerability”. Although pregnant women are able to make informed and conscious choices, they have been considered “vulnerable” due to the potential risks to the fetus, who is also considered as a “patient” [ 22 ]. More recently, with the consideration of pregnant women as “scientifically complex” rather than “vulnerable” subjects, it has been permitted to involve this category in research trials [ 23 ]. The “scientific complexity” reflects both ethical and physiological complexity. The ethical aspects are secondary to the need to find a balance between interests of the fetus and the mother. The physiological aspects are strictly related to the pregnancy status [ 24 ].

Research studies involving pregnant women and fetuses have to satisfy specific federal regulations ( table 2 ). The following appropriate precautions should be taken in research studies involving pregnant women: no pregnant woman may be involved as a subject in a human clinical research project unless the purpose of the research is to meet the health needs of the mother and the fetus will be placed at risk only to the minimum extent necessary to meet such needs, or the risk to the fetus is minimal [ 25 ].

Table 2

Conditions to be met in research studies involving pregnant women and fetuses

Researchers can enrol pregnant women only when the mother and/or the father are legally competent. In fact, the consent to participate in research may be either self-directed (only the mother’s consent is required) or made with the guidance of the woman’s partner. However, the father’s consent need not be obtained when: 1) the research activity is directed to the health needs of the mother; 2) the father’s identity is doubtful; 3) the father is absent; or 4) a pregnancy from rape has occurred [ 26 ]. The consent signature requirements from the mother and father are summarised in table 3 . Once the informed consent is obtained, the pregnant women will be included into any phase of the study unless the research project will be compromised or the patient’s health (mother and/or fetus) will be in danger.

Table 3

Consent signature requirements for pregnant women and children

# : consent requirements are the same whether the risk is “no more than minimal” or “more than minimal”.

Medical students and employees, who take part in numerous aspects of patient care in primary, secondary and tertiary care settings, are often invited to participate in human studies as volunteers. Frequently, the requesting researcher is their supervisor or instructor, who may push them to participate in the study, which can negatively influence their decision and also violate the consent legitimacy. Therefore, in order to protect these subjects against “coercion” or “undue influence”, when an investigator wishes to recruit medical students or employees, they must first obtain IRB approval for inclusion in the study of these vulnerable subgroups [ 27 ].

Prisoners, defined as any individual involuntarily confined or detained in a penal institution, are considered as “vulnerable” because they may be coerced into study participation, and also, due to both cognitive and psychiatric disorders, they can show an impaired ability to provide voluntary informed consent [ 28 ]. To protect this population, the Office for Human Research Protections has stipulated federal regulations according to which the only studies that may involve prisoners are those with independent and valid reasons for involving them ( table 4 ) [ 25 ].

Table 4

Studies that may involve prisoners

Due to the context of war in which they work, as well as the critical care setting in which they are treated, military subjects often receive medical care and/or participate in biomedical research under an “implied consent” condition. Moreover, the superior–subordinate relationship contributes to favour coercion or undue influence, making this population vulnerable [ 29 ]. To curb this phenomenon and to ensure that participation is truly voluntary, the US Dept of Defense agencies have adopted requirements similar to those that govern medical research that applies to the civilian population. Accordingly, the medical research recruitment session happens in the absence of superiors, and the informed consent is obtained prior to participating in a medical research study. The presence of an ombudsman guarantees and verifies that the participation is voluntary and that the information provided during recruitment is complete, accurate and clear. A payment as an incentive is acceptable but it must not be used to legitimise a coercive interference. Additional protection is provided to students at service academies, especially those aged <18 years. However, when emergency research is conducted or the research study advances the development of a medical product needed by the armed forces, informed consent will not be required [ 29 ].

Psychological vulnerability

Mental disability may compromise the self-determination and decision-making capacities [ 30 ]. Researchers interested in enrolling individuals with cognitive disorders are invited to apply different strategies to promote a better understanding of information-gathering processes. Simplifying the questions and content, adopting supportive technologies, using a more simple language, and spending more time for the information process have been suggested as useful and valid measures. When all these strategies prove to be insufficient, the investigators are required to obtain consent from a legally authorised representative [ 30 ].

Social vulnerability

Similarly to other vulnerable populations, research involving the homeless, ethnic minorities, immigrants and refugees is regulated by laws and specific procedures. Cultural and language differences, “undocumented” migrant status, and the precarious legal positions of these subjects raise several ethical issues, such as whether the participation is truly voluntary, or there are unrealistic expectations, or any benefits for their “status”.

Obtaining informed consent in these groups is extremely complex. A friendly procedure has been identified as the best way to adequately involve these vulnerable groups. A health centre or community building could represent an accessible location. The reimbursement of travel expenses for applicants can be a valid solution to obtain a representative sample for the clinical research. Clear and simple language, emphasising confidentiality, with the help of professional interpreters, can tempt migrants to sign the consent form. Lastly, the possibility of receiving something back in return for their contribution may enable successful enrolment of migrants in research [ 31 ].

Special needs: children

Because of their young age as well as their limited emotional and intellectual abilities, children are considered to be legally incompetent to give valid informed consent; thus, to enrol a child in a research study, the permission by at least one parent or legal representative is mandatory ( table 3 ). For subjects aged <18 years, biological or adoptive parents or legal guardians (persons having both legal capacity and responsibility) can give consent on behalf of their child, exercising free power of choice without any form of coercion. While married mothers and fathers both have parental responsibility, unmarried parents can exert parental responsibility only if they are named individually on the child’s birth certificate. Also, divorced parents maintain parental responsibility, but it is necessary to know to whom the child’s custody has been assigned [ 32 ]. However, on this matter, the European laws and regulations are not harmonised and several discrepancies are present in each country [ 33 ].

Despite potential benefits for the research subjects, the failure of parents to give consent (or their refusal to give consent) is not a rare circumstance [ 34 ]. It can be the case that researchers are dealing with underage parents, so that, although underage parents are responsible for representing their children, as minors themselves they are not considered to be sufficiently mature; therefore, they will be not able to give valid consent. Literacy and socioeconomic levels have been identified as the most common reasons for parental non-response [ 34 ]. Clarity and adequate explanation of research information materials should be part of effective planning to overcome language and social barriers.

In clinical studies in which the adopted methodology constitutes “less than minimal risks” for children, passive parental consent represents a possible way to more easily obtain informed parental consent [ 34 ]. Furthermore, parents can be informed with regard to a possible study involving their children, and, at the time of data collection, only the child’s assent is required. In fact, although the child’s decision-making capacity and understanding of the research project in which he/she will be involved may be limited, the Medical Research Council have shown that, when study details are provided and communicated in a clear and adequate manner, the child can be able to reach a decision and participate consciously in the research [ 35 ]. “Assent” is the term coined to express the child’s willingness to participate in clinical trials despite their young age. The “assent” should include and respect the following key points: 1) helping the child to acquire disease awareness; 2) explaining the potential impact of the experimental treatment; 3) evaluating the child’s ability to understand and adapt to new situations or challenges; and 4) positively influencing the patient’s willingness to participate in clinical trials [ 36 ]. Although the “assent” is not mandatory for research offering a direct benefit for the child, it arises from the need to respect paediatric research subjects [ 37 ]. The evaluation of the capacity to provide the “assent” is based on developmental stage, intellectual abilities and life or disease experience. Usually, the cut-off age of 7 years is used for the beginning of logical thought processes and rational decision making [ 38 ]. However, “assent” for children aged <7 years can be also required once the ability to read and write has been verified [ 32 ]. Figures 1 and ​ and2 2 summarise the parental and assent permission requirements, respectively.

Flow chart of parental permission requirements.

Flow chart of child assent requirements.

When conducting clinical research, the obtaining of informed consent is required. Informed consent is a procedure through which a competent subject, after having received and understood all the research-related information, can voluntarily provide his or her willingness to participate in a clinical trial. However, when it is impracticable to obtain consent, and the research does not infringe the principle of self-determination and also provides significant clinical relevance, the researcher is legally authorised to proceed without informed consent. Furthermore, in order to preserve the self-determination and decision-making rights, specific law dispositions are applied when vulnerable populations are enrolled in clinical trials.

Self-evaluation questions

• a) Diagnosis
• b) Risks and benefits of treatment
• c) Alternatives to treatment
• d) Family’s wishes
• a) When a minor is considered as emancipated
• b) When a patient is found to be incompetent
• c) When immediate treatment is necessary to prevent death or permanent impairment
• d) When the subject is aged >18 years
• a) Minor is married or divorced
• b) Minor on active duty in the US armed forces
• c) Minor is considered self-sufficient by a court
• d) Minor having a son

Suggested answers

• All research conducted on humans must be pre-emptively accepted by the subjects themselves through the procedure known as informed consent.
• Voluntary expression of consent and adequate information disclosure about the research are critical and essential elements of the informed consent process.
• When specific circumstances occur, informed consent can be waived: if it is impracticable to obtain consent, if the research does not infringe the principle of self-determination, and if the research provides significant clinical relevance.
• Participation of vulnerable patients in clinical trials is regulated by specific law dispositions.

Conflict of interest: None declared.

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Travel Teams and Other Perils of Parenthood

San Francisco Voters Deliver Blow to Soft-on-Crime Policies

Biden has no israel policy, watch: joe biden's senior moment of the week (vol. 87), biden admin coordinates with unrwa after congress banned taxpayer dollars, state department says, court sides with free beacon, gives gallego 15 days to make case for specific redactions to divorce file, san francisco cited this professor to end 8th grade algebra. her research had 'reckless disregard for accuracy,' complaint alleges., complaint against jo boaler alleges 52 instances of misrepresented research.

A Stanford University professor, whose research was credited with inspiring San Francisco’s failed experiment to ax 8th grade algebra, is facing allegations of "reckless disregard for accuracy" in her work, according to an official academic complaint filed Wednesday with Stanford’s provost and dean of research.

The anonymous complaint , backed by a California-based group of math-and-science focused professionals, alleges that Professor Jo Boaler—the most prominent influence on California’s K-12 math framework that nudges schools away from accelerated math pathways—has in 52 instances misrepresented supporting research she has cited in her own work in order to support her conclusions. These include the notions that taking timed tests causes math anxiety, mixing students of different academic levels boosts achievement, and students have been found to perform better when teachers don’t grade their work. This pattern of "citation misrepresentation," the complaint alleges, violates Stanford’s standards of professional conduct for faculty, showing a disregard for accuracy, and may violate the university's research integrity rules.

"[D]ue to the potential impact and influence Dr. Boaler may have upon the math education of CA K-12 public school students … it is imperative to investigate the allegations of citation misrepresentation in Dr. Boaler’s work," the complaint states.

The allegations come amid backlash against equity-focused educational policies Boaler has championed. The University of California—whose 10 campuses include some of the United States’ most prestigious universities—has reasserted its admissions policy that high school students must take Algebra II, and may no longer swap it with "math-light" data science courses such as those produced by Youcubed, a Stanford center run by Boaler. UC's move drew praise from Silicon Valley executives like Tesla founder Elon Musk and OpenAI CEO Sam Altman. And San Francisco public schools are restoring middle school algebra—which the district axed a decade ago citing Boaler as a major influence—after years of declining student performance.

Wednesday’s complaint alleges that Boaler’s pattern of misrepresenting research citations could violate Stanford’s strict standards of accuracy and academic integrity for its faculty. The university’s research handbook states that the "importance of integrity in research cannot be overemphasized," and stresses that faculty have a "responsibility to foster an environment which promotes intellectual honesty and integrity, and which does not tolerate misconduct in any aspect of research or scholarly endeavor." Stanford deems  "reckless disregard for accuracy" a "misdeed."

"In the case of a serious violation of these standards, a faculty member may face disciplinary charges," the faculty handbook says .

On the question of timed tests causing "math anxiety," Boaler has asserted that "researchers now know that students experience stress on timed tests that they do not experience even when working on the same math questions in untimed conditions." As evidence, she cites a study by psychologist Randall Engle. However, Engle’s paper in question deals with "working memory" rather than student anxiety, and Engle himself called the assessment a "huge misrepresentation" of his work.

Anna Stokke, a mathematics professor at the University of Winnipeg who has studied this claim and found that it contradicts available evidence, said many math teachers nonetheless seem to believe it—and that their belief seems to stem from Boaler.

"I’ve tried to figure out where this misconception comes from among teachers, that timed tests cause math anxiety, and it often seems to lead back to Jo Boaler's faulty opinion piece," Stokke told the Washington Free Beacon .

In other instances, Boaler has said students have "achieved at significantly higher levels" if teachers offered "diagnostic comments" on their work instead of grading them—citing a 1988 study that involved giving a random sample of students a basic language task and some puzzle questions outside of their normal classrooms. The study did not involve an actual academic class taught over the course of several months—a limitation acknowledged by the study’s author but not by Boaler.

Boaler has also claimed that students reached more advanced levels of math, and enjoyed the subject more, if students of all achievement levels learned together. This assertion was reiterated in California’s math framework as a reason to avoid separating advanced students from their lower-performing peers. But the study cited in both cases was not looking solely at the virtues of classroom diversity, but rather the benefits of teaching an accelerated algebra course to all 8th graders in a "diverse suburban school district"—a fact that went unmentioned by Boaler.

Boaler's spokesman Ian McCaleb on Tuesday declined to comment on the complaint before it was filed.

"Dr. Boaler is confident in the integrity and expansiveness of the research that backs her work," he said.

Cole Sampson, a member of the committee that vetted the California framework who has defended its guidelines and the research behind them, said the complaint is an effort by its opponents to "discredit" Boaler.

"While I am not assuming the intent of those I have never met face-to-face, I could imagine why those with opposing views would choose to target and critique the work of Dr. Boaler over all the others who played a pivotal role in the new framework, given her 100K+ followers on social media and the attention (like this report) would draw to their attempt to slow progress of mathematics in the state of California," Sampson said in an email.

Boaler runs a center out of Stanford called Youcubed , which produces data science courses promoted in the California math framework and offers consulting services. Records from one California public school district showed she charged $5,000 per hour in fees. She has also cultivated a high profile in educational and progressive circles. After she drew negative press for the initial drafts of the equity-focused California math framework that she led, she sought help from Democratic megadonor Laurene Powell Jobs to advocate for the guidelines to California governor Gavin Newsom, according to emails.

In correspondence with the Free Beacon , she has downplayed her influence in San Francisco public schools’ 2014 decision to ditch middle school algebra for equity reasons—a policy that was just reversed by San Francisco’s school board and rejected by a voter referendum. Yet she frequently praised the elimination of that course—in a Stanford video , in her research, and op-eds. The district’s former superintendent also credited her research as an inspiration for the policy.

Published under: Education , K-12 , San Francisco , Stanford University

Around Town: Molière’s ‘Tartuffe’ to open April 17 at Laguna Playhouse

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The Laguna Playhouse is presenting a transfer production from North Coast Repertory Theatre of “Tartuffe” by Molière. Previews begin April 17; the play runs through May 5.

Richard Baird will direct the comedy, translated to English verse by Richard Wilbur. Performances are set for Wednesdays through Fridays at 7:30 p.m.; Saturdays at 2 p.m. and 7:30 p.m.; Sundays at 1 p.m. and 5:30 p.m. There will be added performances on Thursday, April 25 at 2 p.m. and Tuesday, April 30 at 7:30 pm. There will be no 5:30 p.m. performance on Sunday, May 5.

Tickets range from $45 to $84 and can be purchased online at lagunaplayhouse.com or by calling (949) 497-2787. Group discounts are available by calling (949) 497-2787, ext. 229. Prices are subject to change.

Laguna Playhouse is located at 606 Laguna Canyon Drive, Laguna Beach.

Caltrans plans work on PCH April 1 through 5

Unless rain or an emergency forces a rescheduling, Caltrans plans to be working on Pacific Coast Highway, between Warner Avenue and Seal Beach Boulevard from 9 a.m. to 3:30 p.m. daily, April 1 through 5.

The project will include concrete barrier removal, replacement and removal of curb ramps, and underground electrical work. Lanes will be closed as the work proceeds.

‘Rasquachismo’ multimedia exhibition champions lowriders

The Huntington Beach Art Center is gearing up for “Rasquachismo,” a multimedia art exhibition devoted to the “aesthetics and transformative power of lowriders,” according to organizers. Laura Black is the curator.

It will be on view from Saturday, April 6 until Saturday, June 1. Visitors to the exhibition will find paintings, a lowrider piñata, print-making and original photography that capture the lowrider spirit. The featured artists are William Camargo with Alkaid Ramirez, Justin Favela, Stephanie Mercado, Arturo Meza II, Aaron Moctezuma, José Manuel Flores Nava, Juliana Rico, Alicia Villegas-Rolon and Cora J. Quiroz.

A public reception is set for 6:30 to 9 p.m. April 6 and will be preceded that afternoon by a car show that will run from 2 p.m. until dusk in the center’s parking lot, 538 Main St., Huntington Beach. Admission is free. Gallery hours are noon to 6 p.m. Tuesday and Wednesday, noon to 8 p.m. Thursday, noon to 5 p.m. Friday and Saturday.

OCC Horticulture will host annual Spring Plant Sale April 5 and 12

The Horticulture Department at Orange Coast College will host its annual Spring Plant Sale on Fridays April 5 and 12, from 9 a.m. to 3 p.m. both days.

The public is invited to visit the horticulture program’s garden nursery to purchase plants that have been produced by students.

“It’s full circle for the students,” Horticulture Instructor and Lab Coordinator Joe Stead said. “They get ownership of the plants and see the seed out to the customer.”

Edible plants such as tomatoes, peppers, strawberries and cooking herbs, as well as other household greens and flowering selections will be available at the sale. All proceeds will go toward student scholarships and projects.

The college is located at 2701 Fairview Road, Costa Mesa. Park in Lot H or G.

First responders Picklefest set for April 13 in Newport Beach

Club founder Sean Bollettieri will host the second annual First Responders Picklefest Saturday, April 13, at the private Tennis + Pickleball Club at Newport Beach, 11 Clubhouse Drive.

All first responders are welcome and encouraged to create a team and play for the Ultimate Picklefest Championship. To learn more, call (949) 759-0711.

Marissa Sur pegged as Huntington Beach director of human resources

Marissa Sur was selected this week as the director of human resources in Huntington Beach, after previously serving as a human resources manager in Newport Beach.

In her role, Sur will be responsible for directing, planning, organizing and managing the personnel functions and programs of Huntington Beach. She will oversee programs and services including employee relations, labor negotiations, recruitment and selection, classification and compensation, training, benefits and more.

Sur has a bachelor’s degree in criminal justice from Cal State Long Beach.

New director of Costa Mesa Parks & Community Services named

Brian Gruner, a 24-year veteran of municipal government, has been appointed as Costa Mesa’s new Director of Parks & Community Services, it was announced this week by City Manager Lori Ann Farrell Harrison.

Gruner, who started as part-time recreation leader has extensive experience in the management of Parks, Recreation and Community Services, including the oversight of multimillion-dollar budgets, capital improvement projects, strategic planning, community outreach, partnership development and arts and cultural programs.

He most recently served as superintendent of parks and recreation for the city of Fairfield, Calif. He has also worked for Laguna Woods Village and the city of Mission Viejo.

“I’m excited to be relocating back to Orange County and being part of the city of Costa Mesa team,” Gruner said. “Having grown up in Orange County, I have fond memories of Costa Mesa from competing in tennis tournaments at the Costa Mesa Tennis Center, enjoying the Orange County Fair and swap meets, shopping at South Coast Plaza, playing golf at the Costa Mesa Country Club and enjoying the natural beauty of Fairview Park.”

Gruner holds a bachelor’s degree from Cal State Fullerton in business management and a master’s in business administration from the University of Phoenix.

Tour de Saddleback raises $1,300 for pediatric cancer research

The Tour de Saddleback on March 23 drew 302 participants who rode through Orange County while raising more than $1,300 for Irvine-based Pediatric Cancer Research Foundation , officials announced this week.

The tour took riders through Laguna Hills, Santiago Canyon, Rancho Santa Margarita and Irvine. The ride started and finished at Irvine Valley College.

“With this only being our second year of producing the Tour de Saddleback, I couldn’t be more thrilled with the outcome,” said Mike Bone, president and chief executive of Spectrum Sports Management, which produces the annual event. “It was amazing to see so many people enjoying the beauty of our community while raising funds for a great organization.”

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