critical appraisal of research examples

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Eldredge J. Evidence Based Practice: A Decision-Making Guide for Health Information Professionals [Internet]. Albuquerque (NM): University of New Mexico Health Sciences Library and Informatics Center; 2024.

Evidence Based Practice: A Decision-Making Guide for Health Information Professionals [Internet].

Critical appraisal.

Critical Appraisal: Wall Street. Bryce Canyon National Park. Utah

The goal of researchers should be to create accurate and unbiased representations of selected parts of reality. The goal of HIPs should be to critically examine how well these researchers achieve those representations of reality. Simultaneously, HIPs should gauge how relevant these studies are to answering their own EBP questions. In short, HIPs need to be skeptical consumers of the evidence produced by researchers.

This skepticism needs to be governed by critical thinking while recognizing that there are no perfect research studies . The expression, “The search for perfectionism is the enemy of progress,” 1 certainly applies when critically appraising evidence. HIPs should engage in “Proportional Skepticism,” meaning that finding minor flaws in a specific study does not automatically disqualify it from consideration in the EBP process. Research studies also vary in quality of implementation, regardless of whether they are systematic reviews or randomized controlled trials (RCTs). Proportional Skepticism acknowledges that some study designs are better than others at accurately representing parts of reality and answering different types of EBP questions. 2

This chapter provides tips for readers in their roles as consumers of evidence, particularly evidence produced by research studies. First, this chapter explores the various forms of bias that can cloud the representation of reality in research studies. It then presents a brief overview of common pitfalls in research studies. Many of these biases and pitfalls can easily be identified by how they might manifest in various forms of evidence, including local evidence, regional or national comparative data, and the grey literature. The emphasis in this chapter, however, is on finding significant weaknesses in research-generated evidence, as these can be more challenging to detect than in the other forms of evidence. Next, the chapter further outlines the characteristics of various research studies that might produce relevant evidence. Tables summarizing the major advantages and disadvantages of specific research designs appear throughout the chapter. Finally, critical appraisal sheets serve as appendices to the chapter. These sheets provide key questions to consider when evaluating evidence produced by the most common EBP research study designs.

• 4.1 Forms of Bias

Researchers and their research studies can be susceptible to many forms of bias, including implicit, structural, and systemic biases. These biases are deeply embedded in society and can inadvertently appear within research studies. 3 , 4 Bias in research studies can be defined as the “error in collecting or analyzing data that systematically over- or underestimates what the researcher is interested in studying.” 5 In simpler terms, bias results from an error in the design or conduct of a study. 6 As George Orwell reminds us, “..we are all capable of believing things we know to be untrue….” 7 Most experienced researchers are vigilant to avoid these types of biases, but biases can unintentionally permeate study designs or protocols irrespective of the researcher’s active vigilance. If researchers recognize these biases, they can mitigate them during their analyses or, at the very least, they should account for them in the limitations section of their research studies.

Expectancy Effect

For at least 60 years, behavioral scientists have observed a consistent phenomenon: when a researcher anticipates a particular response from someone, the likelihood of that person responding in the expected manner significantly increases. 8 This phenomenon, known as the Expectancy Effect, can be observed across research studies, ranging from interviews to experiments. In everyday life, we can observe the Expectancy Effect in action, such as when instructors selectively call on specific students in a classroom 9 , 10 or when the President or Press Secretary at a White House press conference chooses certain reporters while ignoring others. In both instances, individuals encouraged to interact with either the teacher or those conducting the press conference are more likely to seek future interactions. Robert Rosenthal, the psychologist most closely associated with uncovering and examining instances of the Expectancy Effect, has extensively documented these self-fulfilling prophecies in various everyday situations and within controlled research contexts. 11 , 12 , 13 , 14 It is important to recognize that HIP research studies have the potential to be influenced by the Expectancy Effect.

Hawthorne Effect

Participants in a research study, when aware of being observed by researchers, tend to behave differently than they would in other circumstances. 15 , 16 This phenomenon, known as the Hawthorne Effect, was initially discovered in an obscure management study conducted at the Hawthorne Electric Plant in Chicago. 17 , 18

The Hawthorne Effect might be seen in HIP participant-observer research studies where researchers monitor interactions such as help calls, chat sessions, and visits to a reference desk. In such studies, the employees responding to these requests might display heightened levels of patience, friendliness, or accommodation due to their awareness of being observed, which aligns with the Hawthorne Effect. It is important to note that the Hawthorne Effect is not inevitable, 19 and there are ways for researchers to mitigate its impact. 20

Historical events have the power to significantly shape research results. A compelling illustration of this can be found in the context of the COVID-19 pandemic, which left a profound mark on society. The impact of this crisis was so significant that a research study on attitudes toward infectious respiratory disease conducted in 2018 would likely yield different results compared to an identical study conducted in 2021, when society was cautiously emerging from the COVID-19 pandemic. Another instance demonstrating the impact of historical events is the banking crisis and recession of 2008-2009. Notably, two separate research studies on the most important research questions facing HIPs, conducted in 2008 and 2011, respectively, for the Medical Library Association Research Agenda, had unexpected differences in results. 21 The 2011 study identified HIPs as far more concerned about issues of economic and job security than the 2008 study. 22 The authors of the 2011 study specifically attributed the increased apprehension regarding financial insecurity to these historical events related to the economy. Additionally, historical events also can affect research results over the course of a long-term study. 23

During the course of longitudinal research studies, participants might experience changes in their attitudes or their knowledge. These changes, known as Maturation Effects, can sometimes be mistaken as outcomes resulting from specific events or interventions within the research study. 24 For instance, this might happen when a HIP provides instruction to first-year students aimed at fostering a positive attitude toward conducting literature searches. Following a second session on literature searching for second-year students, an attitudinal survey might indicate a higher opinion of this newly-learned skill among medical students. At this point, one might consider whether this attitude change resulted from the two instructional sessions or if there were other factors at play, such as a separate required course on research methods or other experiences of the students between the two searching sessions. In such a case, one would have to consider attributing the change to the Maturation Effect. 25

Misclassification

Misclassification can occur at multiple junctures in a research study, including when enrolling the participants, collecting data from participants, measuring exposures or interventions, or recording outcomes. 26 Minor misclassifications can introduce outsized distortions in any one of these junctures due to the multiple instances involved. The simple task of defining a research population can introduce the risk of misclassification, even among conscientious HIP researchers. 27

HIPs work with emerging information technologies far more than any other health sciences profession. Part of this work involves assessing the performance of these new information technologies as well as working on making adaptations to these technologies. Given the frequency that HIPs work with these new technologies, there remains the potential for novelty bias to arise, which refers to the initial fascination and perhaps even an enthusiasm towards innovations during their early phases of introduction and initial use. 28 This bias has been observed in publications from various health professions, spanning a wide range of innovations, such as dentistry tooth implants 29 or presentation software. 30

Many HIPs engage in partnerships with corporate information technology firms or other external organizations to pilot new platforms. These partnerships often result in reports on these technologies, typically case reports or new product reviews. Given the nature of these relationships, it is important for all authors to provide clear conflict of interest statements. For many HIPs, however, novelty bias is still an occupational risk due to their close involvement with information technologies. To mitigate this bias, HIPs can implement two strategies: increasing the number of participants in studies and continuing to try (often unsuccessfully) to replicate any initial rosy reports. 31

Recall Bias

Recall Bias poses a risk to study designs such as surveys and interviews, which heavily rely on the participants’ ability to recollect past events accurately. The wording of surveys and questions posed by interviewers can inadvertently direct participants’ attention to certain memories, thereby distorting the information provided to researchers. 32

Scalability Bias

Scalability Bias fails to consider the applicability of a study carried out in one specific context when transferred to another context. Shadish et al 33 identify two forms: Narrow-to-Broad Bias and Broad-to-Narrow Bias.

Narrow-to-Broad Bias applies findings in one setting and suggests that these findings apply to many other settings. For example, a researcher might attempt to depict the attitudes of all students on a large campus based on the interview of a single student or by surveying only five to 15 students who belong to a student interest group. Broad-to-Narrow Bias makes the inverse mistake by assuming that what generally applies to a large population should apply to an individual or a subset of that population. In this case, a researcher might conduct a survey on a campus to gauge attitudes toward a subject and assume that the general findings apply to every individual student. Readers familiar with classical training in logic or rhetoric will recognize these two biases as the Fallacy of Composition and the Fallacy of Hasty Generalization, respectively. 34

Selection Bias

Selection Bias happens when information or data collected in a research study does not accurately or fully represent the population of interest. It emerges when a sample distorts the realities of a larger population. For example, if a survey or a series of interviews with users only include friends of the researcher, it would be susceptible to Selection Bias, as it fails to encompass the broader range of attitudes present in the entire population. Recruitment into a study might occur only through media that are followed by a subset of the larger demographic profile needed. Engagement with an online patient portal, originally designed to mitigate Selection Bias in a particular study, unexpectedly gave rise to racial disparities instead. 35

Selection Bias can originate from within the study population itself, leading to potential distortions in the findings. For example, only those who feel strongly, either negatively or positively, towards a technology might volunteer to offer opinions on it. Selection Bias also might occur when an interviewer, for instance, either encourages interviewees or discourages interviewees from speaking on a subject. In all these cases, someone exerts control over the focus of the study that then misrepresents the actual experiences of the population. Rubin 36 reminds us that systemic and structural power structures in society exert control over what perspectives are heard in a research study.

While there are many other types of bias, the descriptions explained thus far should equip the vigilant consumer of research evidence with the ability to detect potential weaknesses across a wide range of HIP research articles.

• 4.2 Other Research Pitfalls

A cause is “an antecedent event, condition, or characteristic” that precedes an outcome. A sufficient cause provides the prerequisites for an outcome to occur, while a necessary cause must exist before the outcome can occur. 37 These definitions rely on the event, condition, or characteristic to precede the outcome temporally. At the same time, the cause and its outcome must comply with biological and physical laws. There must also be a plausible strength of the association, and the link between the putative cause and the outcome must be replicable across varied instances. 38 , 39 In the past century, philosophers and physicists have examined the concept of causality exhaustively, while 40 the concept of causality has been articulated over the past 70 years in the health sciences. 41 HIPs should keep these guidelines in mind when critically appraising any claims that an identified factor “caused” a specific outcome.

Confounding

Confounding relates to the inaccurate linkage of a possible cause to an identified outcome. It means that another concurrent event, condition, or characteristic actually caused the outcome. One instance of confounding might be an advertised noontime training on a new information platform that also features a highly desirable lunch buffet. The event planners might mistakenly assume that the high attendance rate stemmed from the perceived need for the training, while the primary motivation actually was the lunch buffet. In this case, the lunch served as a confounder.

Confounding presents the most significant alternative explanation to biases when trying to determine causation. 42 One recurring EBP question that arises among HIPs and academic librarians pertains to whether student engagement with HIPs and the use of information resources leads to student success and higher graduation rates. A research team investigated this issue and found that student engagement with HIPs and information resources did indeed predict student success. During the process, they were able to identify and eliminate potential confounders that might explain student success, such as high school grade point average, standardized exams, or socioeconomic status. 43 It turns out that even artificial intelligence can be susceptible to confounding, although it can “learn” to overcome those confounders. 44 Identifying and controlling for potential confounders can even resolve seemingly intractable questions. 45 RCTs are considered far superior in controlling for known or unknown confounders than other study designs, so they are often considered to be the highest form of evidence for a single intervention study. 46

Study Population

When considering a research study as evidence for making an EBP decision, it is crucial to evaluate whether the study population closely and credibly resembles your own user population. Each study design has specific features that can help answer this question. There are some general questions to consider that will sharpen one’s critical appraisal skills.

One thing to consider is whether the study population accurately represents the population it was drawn from. Are there any concerns regarding the sample size, which might make it insufficient to represent the larger population? Alternatively, were there issues with how the researchers publicized or recruited participants? 47 Selection Bias, mentioned earlier in this chapter, might contribute to the misrepresentation of a population if the researchers improperly included or excluded potential participants. It is also important to evaluate the response rate—was it too low, which could potentially introduce a nonresponse bias? Furthermore, consider whether the researchers’ specific incentives to enroll in the study attracted nonrepresentative participants.

HIPs should carefully analyze how research study populations align with their own user populations. In other words, what are the essential relevant traits that a research population might share or not share with a user population?

Validity refers to the use of an appropriate study design with measurements that are suitable for studying the subject. 48 , 49 It also applies to the appropriateness of the conclusions drawn from the research results. 50 Researchers devote considerable energy to examining the validity of their own studies as well as those conducted by others, so validity generally resides outside the scope of this guide intended for consumers of the research evidence.

Two brief examples might convey the concept of validity. In the first example, instructors conducting a training program on a new electronic health record system might claim success based on the number of providers they train. A more valid study, however, would include clear learning objectives that lead to demonstratable skills, which can be assessed after the training. Researchers could further extend the validity by querying trainees about their satisfaction or evaluating these trainees’ skills two weeks later to gauge the retention of the training. As a second example, a research study on a new platform might increase its validity by merely not reporting the number of visits to the platform. Instead, the study could gauge the level of user engagement through factors such as downloads, time spent on the platform, or the diversity of users.

• 4.3 Study Designs

Study designs, often referred to as “research methods” in journal articles or presentations, serve as the means to test researchers’ hypotheses. Study designs can be compared to tools such as hammers, screwdrivers, saws, or utensils used in a kitchen. Both analogies emphasize the importance of using the appropriate tool or utensil for the task at hand. One would not use a hammer when a saw would be a better choice, nor would one use a spatula to ladle a cup of soup from a pot. Similarly, researchers need to take care to use study designs best suited for the research question. Likewise, HIPs engaged in EBP should recognize the suitability of study designs in answering their EBP questions. The following section provides a review of the most common study designs 51 employed to answer EBP questions, which will be further discussed in the subsequent chapter on decision making.

Types of EBP Questions

There are three major types of EBP questions that repeatedly emerge from participants in continuing education courses: Exploration, Prediction, and Intervention. Coincidentally, these major types of questions also exist in research agendas for our profession. 52 Different study designs have optimal applicability in addressing the aforementioned issues of validity and in controlling biases for each type of question.

Exploration Questions

Exploration questions are frequently concerned with understanding the reasons behind certain phenomena and often begin with “Why.” For example, a central exploration question could be, “Why do health care providers seek health information?” Paradoxically, exploration “Why” research studies often do not ask participants direct “why” questions because this approach often leads to unproductive participant responses. 53 Other exploration questions might include:

• What are the specific Point-of-Care information needs of our front-line providers?
• Why do some potential users choose never to use the journals, books, and other electronic resources that we provide?
• Do our providers find the alerts that automatically populate their electronic health records useful?

Prediction Questions

Prediction questions aim to forecast future needs based on past patterns, and HIPs frequently pose such inquiries. These questions attempt to draw a causal connection between events, conditions, or characteristics in the present with outcomes in the future. Examples of prediction questions might include:

• To what extent do students retain their EBP question formulation and searching skills after two years?
• Do hospitals that employ HIPs produce better patient outcomes, as indicated by measures such as length of stay, mortality rates, or infection rates?
• Which archived committee meeting minutes within my organization are likely to be utilized within the next 30 years?

Intervention Questions

Intervention questions aim to distinguish between different potential courses of action to determine their effectiveness in achieving specific desirable outcomes. Examples of intervention questions might include:

• Does providing training on EBP question formulation and searching lead to an increase in information-seeking behavior among public health providers in rural practices?
• Which instructional approach yields better performance among medical students on standardized national licensure exams: didactic lecture or active learning with application exercises?
• Which Point-of-Care tool, DynaMed or UpToDate, generates more answers to patient care questions and higher provider satisfaction?

Case Reports

Case reports ( Table 1 ) are prevalent in the HIP literature and are often referred to interchangeably as “Case Studies.” 54 They are records of a single program, project, or experience, 55 with a particular focus on new developments or programs. These reports provide rich details on a single instance in a narrative format that is easy to understand. When done correctly, they can be far more challenging to develop than expected, contrary to the misconception that they are easy to assemble. 56 The most popular case reports revolve around innovation, which is broadly defined as “an idea, practice, or object” perceived to be new.” 57 A HIP innovation might be a new information technology, management initiative, or outreach program. A case report might also be the only available evidence due to the newness of the innovation, and in some rare instances, a case report might be the only usable evidence. For this reason, case reports hold the potential to point to new directions or emerging trends in the profession.

While case reports can serve an educational purpose and are generally interesting to read, they are not without controversy. Some researchers do not consider case reports as legitimate sources of research evidence, 58 and practitioners often approach them with skepticism. There are many opportunities for authors to unintentionally introduce biases into case reports. Skeptical practitioners criticize the unrealistic and overly positive accounts of innovations found in some case reports.

Case reports focus solely on a single instance of an innovation or noteworthy experience. 59 As a pragmatic matter, it can be difficult to justify adopting a program based on a case report carried out in one specific and different context. To illustrate the challenges of using case reports statistically, consider a hypothetical scenario: HIPs at 100 institutions might attempt to implement a highly publicized new information technology. HIPs at 96 of those institutions experience frustration at the poor performance of the new technology, and many eventually abandon it. Meanwhile, in this scenario, HIPs at four institutions present their highly positive case reports on their experiences with the new technology at an annual conference. These reports subsequently appear in the literature six months later. While these four case reports do not even reach the minimum standard for statistical significance, they become part of the only evidence base available for the new technology, thereby gaining prominence solely from “Survivor Bias” as they alone continued when most efforts to implement the new technology had failed. 60 , 61

Defenders of case reports argue that some of these issues can be mitigated when the reports include more rigorous elements. 62 , 63 For instance, a featured program in a case report might detail how carefully the authors evaluated the program using multiple meaningful measurements. 64 Another case report might document a well-conducted survey that provides plausible results in order to gauge peoples’ opinions. Practitioners tend to view case reports more favorably when they provide negative aspects of the program or innovation, framing them as “lessons learned.” Multiple authors representing different perspectives or institutions 65 seem to garner greater credibility. Full transparency, where authors make foundational documents and data available to readers, further bolsters potential applicability. Finally, a thorough literature review of other research studies, providing context and perhaps even external support for the case report’s results, can further increase credibility. 66 All of these elements increase the likelihood that the featured case report experience could potentially be transferred to another institution.

Case reports gain greater credibility, statistical probability, and transferability when combined with other case reports on the same innovation or similar experience, forming a related, although separate, study design known as a case series. Similar to case reports, case series gain greater credibility when their observations across cases are accompanied by literature reviews. 67

Interviews ( Table 2 ) are another common HIP research design. Interviews aim to understand the thoughts, preferences, or feelings of others. Interviews take different forms, including in-person or remote settings, as well as structured or unstructured questionnaires. They can involve one interviewer and one interviewee or a small team of interviewers who conduct group interviews, often referred to as a focus group. 68 , 69 , 70 While interviews technically fall under the category of surveys, they are discussed separately here due to their popularity in the HIP literature and the unique role of the interviewer in mediating and responding to interviewees.

Interviews can be highly exploratory, allowing researchers to discover unrecognized patterns or sentiments regardless of format. They might uniquely be able to answer “why?” research questions or probe interviewees’ motivations. 71 Interviews can sometimes lead to associations that can be further tested using other study designs. For instance, a set of interviews with non-hospital-affiliated practitioners about their information needs 72 can lead to an RCT comparing preferences for two different Point-of-Care tools. 73

Interviews have the potential to introduce various forms of biases. To minimize bias, researchers can employ strategies such as recruiting a representative sample of participants, using a neutral party to conduct the interviews, following a standardized protocol to ensure participants are interviewed equitably, and avoiding leading questions. The flexibility for interviewers to mediate and respond offers the strength to discover new insights. On balance, this flexibility also carries the risk of introducing bias if interviewers inject their own agendas into the interaction. Considering these potential biases, interviews are ranked below descriptive surveys in the Levels of Evidence discussed later in this chapter. To address concerns about bias, researchers should ensure that interviews thoroughly document and analyze all de-identified data collected in a transparent manner, allowing practitioners reviewing these studies to detect and mitigate any potential biases.

Descriptive Surveys

Surveys are an integral part of our society. Every ten years, Article 1, Section 2 of the United States Constitution requires everyone living in the United States to report demographic and other information about themselves as part of the Census. Governments have been taking censuses ever since ancient times in Babylon, Egypt, China, and India. 74 , 75 While censuses might offer highly accurate portrayals, they are time-consuming, complex, and expensive endeavors.

Most descriptive surveys involve polling a finite sample of the population, making sample surveys less time-consuming and less expensive compared to censuses. Surveys involving samples, however, are still complex. Surveys can be defined as a method for collecting information about a population of people. 76 They aim to describe, compare, or explain individual and societal knowledge, feelings, values, preferences, and behaviors.” 77 Surveys are accessed by respondents without a live intermediary administering them. For participants, surveys are almost always confidential and are often anonymous. There are three basic types of surveys: descriptive, change metric, and consensus.

Descriptive surveys ( Table 3 ) elicit respondents’ thoughts, emotions, or experiences regarding a subject or situation. Cross-sectional studies are one type of descriptive survey. 78 , 79 Change metric surveys are part of a cohort or experimental study where at least one survey takes place prior to an exposure or intervention. Later on during the study, the same participants are surveyed again to assess any changes or the extent of change. Sometimes, change metric surveys gauge the differences between user expectations and actual user experiments in surveys, known as Gap Analyses. Change metric surveys resemble descriptive surveys. They are discussed in subsequent study designs later in this chapter. The aim of consensus surveys is to facilitate agreement among groups regarding collective preferences or goals, even in situations where initial consensus might seem elusive. Consensus survey techniques on decision-making in EBP will be discussed in the next chapter.

Descriptive surveys are likely the most utilized research study design employed by HIPs. 80 The common use of surveys by HIP researchers and in society at large is one of the greatest weaknesses of descriptive surveys. While surveys are familiar, they have numerous pitfalls and limitations. 81 , 82 , 83 Even when large-scale public opinion surveys are conducted by experts, discrepancies often exist between survey results and actual population behavior, as evidenced by repeated erroneous election predictions by veteran pollsters. 84

Beyond the inherent limitations of survey designs, there are multiple points where researchers can unintentionally introduce bias or succumb to other pitfalls. Problems can arise at the outset when researchers design a survey without conducting an adequate literature review to consider the previous research on the subject. The survey instrument itself might contain confusing or misleading questions, including asking leading questions that elicit a “correct” answer rather than a truthful response. 85 , 86 For example, a question about alcohol consumption in a week might face validity issues due to social stigma. The recruitment process and the characteristics of participants can also introduce Selection Bias. 87 The introduction of the survey of the medium through which participants interact with the survey might underrepresent some demographic groups based on age, gender, class, or ethnicity. It is also important to consider the representativeness of the sample in relation to the target population. Is the sample large enough? 88 Interpreting survey results, particularly answers to open-ended questions, can also distort the study results. Regardless of how straightforward surveys might appear to participants or to the casual observer, they are oftentimes complex endeavors. 89 It is no wonder that the classic Survey Kit consists of 10 volumes to explain all the details that need to be attended to for a more successful survey. 90

Cohort Studies

Cohort studies ( Table 4 ) are one of several observational study designs that focus on observing possible causes (referred to as “exposures”) and their potential outcomes within a specific population. In cohort studies, investigators collect observations, usually in the form of data, without directly interjecting themselves into the situation. Cohort members are identified without the need for the explicit enrollment typically required in other designs. Figure 1 depicts the elements of a defined population, the exposure of interest, and the hypothesized outcome(s) in cohort studies. Cohort studies are fairly popular HIP research designs, although they are rarely labeled as such in the research literature. Cohort studies can be either prospective or retrospective. Retrospective cohort studies are conducted after the exposure has already occurred to some members of a cohort. These studies focus on examining past exposures and their impact on outcomes. 91

Cohort Study Design. Copyright Jonathan Eldredge. © 2023.

Many HIPs conducting studies on resource usage employ the retrospective cohort design. These studies link resource usage patterns to past exposures that might explain the observed patterns. That exposure might be a feature in the curriculum that requires learners to use that resource, or it could be an institutional expectation for employees to complete an online training module, which affects the volume of traffic on the module. On the other hand, prospective cohort studies begin in the present by identifying a cohort within the larger population and observing the exposure of interest and whether this exposure leads to an identified outcome. The researchers are collecting specific data as the cohort study progresses, including whether cohort members have been exposed and, if so, the duration or intensity of the exposure. These varied levels of exposure might be likened to different drug dosages.

Prospective cohort studies are generally regarded as less prone to bias or confounding than retrospective studies because researchers are intentional about collecting all measures throughout the study period. In contrast, retrospective studies are dependent on data collected in the past for other purposes. Those pre-existing compiled data sets might have missing elements necessary for the retrospective study. For example, in a retrospective cohort study, usage or traffic data on an online resource might have been originally collected by an institution to monitor the maintenance, increase, or decrease in the number of licensed simultaneous users. These data were originally gathered for administrative purposes, rather than for the primary research objectives of the study. Similarly, in a retrospective cohort study investigating the impact of providing tablets (exposure) to overcome barriers in using a portal (outcome), there might be a situation where the inventory system, initially created to track the distribution of tablets, is repurposed for a different objective, such as video conferencing. 92 Cohort studies regularly use change metric surveys, as discussed above. Prospective cohort studies are better at monitoring cohort members over the study duration, while retrospective cohort studies do not always have a clearly identified cohort membership due to the possible participant attrition not recorded in the outcomes. For this reason, plus the potentially higher integrity of the intentionally collected data, prospective cohort studies tend to be considered a higher form of evidence. The increased use of electronic inventories and the collection of greater amounts of data sometimes means that a data set created for one purpose can still be repurposed for a retrospective cohort study.

Quasi-Experiment

In contrast to observational studies like cohort studies, which involve researchers simply observing exposures and then measuring outcomes, quasi-experiments ( Table 5 ) include the active involvement of researchers in an intervention that is an intentional exposure. In quasi-experiments, researchers deliberately intervene and engage all members of a group of participants. 93 These interventions can take the form of training programs or work requirements that involve participants interacting with a new electronic resource, for example. Quasi-experiments are often employed by instructors who pre-test a group of learners, provide them with training on a specific skill or subject, and then conduct a post-test to measure the learners’ improved level of comprehension. 94 In this scenario, there is usually no explicit comparison with another untrained group of learners. The researchers’ active involvement tends to reduce some forms of bias and other pitfalls. Confounding, nevertheless, represents one looming potential weakness in quasi-experiments since a third unknown factor, a confounder, might be associated with the training and outcome but goes unrecognized by the researchers. 95 Quasi-experiments do not use randomization, which also can eliminate most confounders.

Quasi-Experiments

Randomized Controlled Trials (RCTs)

RCTs ( Table 6 ) are highly effective in resolving a choice between two seemingly reasonable courses of action. RCTs have helped answer some seemingly unresolvable HIP decisions in the past, including:

Randomized Controlled Trails (RCTs)

• Do embedded clinical librarians OR the availability of a reference service improve physician information-seeking behavior? 96 , 97
• Does weeding OR not weeding a collection lead to higher usage in a physical book collection? 98
• Does training in Evidence Based Public Health skills OR the lack of this training lead to an increase in public health practitioners’ formulated questions? 99

Paradoxically, RCTs are relatively uncommon in the HIP evidence base despite their powerful potential to resolve challenging decisions. 100 One explanation might be that, in the minds of the public and many health professionals, RCTs are often associated with pharmaceutical treatments. Researchers, however, have used RCTs far more broadly to resolve questions about devices, lifestyle modifications, or counseling in the realm of health care. Some HIP researchers believe that RCTs are too complex to implement, and some even consider RCTs to be unethical. These misapprehensions should be resolved by a closer reading about RCTs in this section and in the referenced sources.

Some HIPs, in their roles as consumers of research evidence, consider RCTs too difficult to interpret. This misconception might stem from the HIPs’ past involvement in systematic review teams that have evaluated pharmaceutical RCTs. Typically, these teams use risk-of-bias tools, which might appear overly complex to many HIPs. The most commonly used risk-of-bias tool 101 for critically appraising pharmaceutical RCTs appears to be published by Cochrane, particularly its checklist for identifying sources of bias. 102 Those HIPs involved with evaluating pharmaceutical RCTs should familiarize themselves with this resource. This section of Chapter 4 focuses instead on aspects of RCTs that HIPs might encounter in the HIP evidence base.

A few basic concepts and explanations of RCT protocols should alleviate any reluctance to use RCTs in the EBP Process. The first concept of equipoise means that researchers undertook the RCT because they were genuinely uncertain about which course of action among the two choices would lead to the more desired outcomes. Equipoise has practical and ethical dimensions. If prior studies have demonstrated a definitively superior course of action between the two choices, researchers would not invest their time and effort in pursuing an already answered question unless they needed to replicate the study. From an ethical perspective, why would researchers subject control group participants to a clearly inferior choice? 103 , 104 The background or introduction section of an article about RCTs should establish equipoise by drawing on evidence from past studies.

Figure 2 illustrates that an RCT begins with a representative sample of the larger population. Many consumers of RCTs should bear in mind that the number of participants in a study depends on more than a “magic number”; it also relies on the availability of eligible participants and the statistical significance of any differences measured. 105 , 106 , 107 , 108 Editors, peer reviewers, and statistical consultants at peer-reviewed journals play a key role in screening manuscripts for any major statistical problems.

Randomized Controlled Trial.

Recruiting a representative sample can be a challenge for researchers due to the various communication channels used by different people. Consumers of RCTs should be aware of these issues since they affect the applicability of any RCT to one’s local setting. Several studies have documented age, gender, socioeconomic, and ethnic underrepresentation in RCTs. 109 , 110 , 111 , 112 , 113 One approach to addressing this issue is to tailor the incentives for participation based on the appeals to different underrepresented groups. 114 Close collaboration with underrepresented groups through community outreach also can help increase participation. Many RCTs include a table that records the demographic representation of participants in the study, along with the demographic composition of those who dropped out. HIPs evaluating an RCT can scrutinize this table to assess how closely the study’s population aligns with their own user population. RCTs oftentimes screen out potential participants who are unlikely to adhere to the study protocol or who are likely to drop out. Participants who will be unavailable during key study dates might also be removed. HIP researchers might want to exclude potential participants who have prior knowledge of a platform under study or who might be repeating an academic course where they were previously exposed to the same content. These preliminary screening measures cannot anticipate all eventualities, which is why some articles include a CONSORT diagram to provide a comprehensive overview of the study design. 115

RCTs often control for most biases and confounding through randomization . Imagine you’re in the tenth car in a right-hand lane approaching a traffic signal at an intersection, and no one ahead of you uses their turn signal. You want to take a right turn immediately after the upcoming intersection. In this situation, you don’t know which cars will actually turn right and which ones will proceed straight. If you want to stay in the right-hand lane without turning right, you can’t predict who will slow you down by taking a right or who will continue at a faster pace straight ahead to your own turnoff. This scenario is similar to randomization in RCTs because, just like in the traffic situation, you don’t know in advance which participants will be assigned to each course of action. Randomization ensures that each participant has an equal chance of being assigned to either group regardless of the allocation of others before them, effectively eliminating the influence of bias, confounding, or any other unknown factors that could impact the study’s outcomes.

Contamination poses a threat to the effectiveness of the randomization. It occurs when members of the intervention or control groups interact and collaborate, thereby inadvertently altering the intended effects of the study. RCTs normally have an intervention group that receives a new experience, which will possibly lead to more desired outcomes. The intervention can involve accessing new technology, piloting a new teaching style, receiving specialized training content, or other deliberate actions by the researchers. On the other hand, control group members typically receive the established technology, experience the usual teaching techniques, receive standard training content, or have the usual set of experiences.

Contamination might arise when members of the intervention and control groups exchange information about their group’s experiences. Contamination interferes with the researchers deliberately treating the intervention and control groups differently. For example, in an academic setting, contamination might happen if the intervention group receives new training while the control group receives traditional training. In a contamination scenario, members of the two groups would exchange information. When their knowledge or skills are tested at the end of the study, the assessment might not accurately reflect their comparative progress since both groups have been exposed to each other’s training. A Delphi Study generated a list of common sources of contamination in RCTs, including participants’ physical proximity, frequent interaction, and high desirability of the intervention. 116 Information technology can assist researchers in avoiding, or at least countering, contamination by interacting with study participants virtually rather than in a physical environment. Additionally, electronic health records can similarly be employed in studies while minimizing contamination. 117

RCTs often employ concealment (“blinding”) techniques to ensure that participants, researchers, statisticians, and other analysts are unaware of which participants are enrolled in either the intervention or control groups. Concealment prevents participants from deviating from the protocols. Concealment also reduces the likelihood that the researchers, statisticians, or analysts interject their views into the study protocol, leading to unintended effects or biases. 118

Systematic Reviews

Systematic reviews ( Table 7 ) strive to offer a transparent and replicable synthesis of the best evidence to answer a narrowly focused question. They often involve exhaustive searches of the peer-reviewed literature. While many HIPs have participated in teams conducting systematic reviews, these efforts primarily serve health professions outside of HIP subject areas. 119 Systematic reviews can be time-consuming and labor-intensive endeavors. They rely on a number of the same critical appraisal skills covered in this chapter and its appendices to evaluate multiple studies.

Systematic reviews can include evidence produced by any study design except other reviews. Producers of systematic reviews often exclude study designs more prone to biases or confounding when a sufficient number of studies with fewer similar limitations are available. Systematic reviews are popular despite being relatively limited in number. If well-conducted, they can bypass the first three steps of the EBP Process and position the practitioner well to make an informed decision. The narrow scope of systematic reviews, however, does limit their applicability to a broad range of decisions.

Nearly all HIPs have used the findings of systematic reviews for their own EBP questions. 120 Since much of the HIP evidence base exists outside of the peer-reviewed literature, systematic reviews on HIP subjects can include grey literature, such as presented papers or posters from conferences or white papers from organizations. The MEDLINE database has a filter for selecting systematic reviews as an article type when searching the peer-reviewed literature. Unfortunately, this filter sometimes mistakenly includes meta-analyses and narrative review articles due to the likely confusion among indexers regarding the differences between these article types. It is important to note that meta-analyses are not even a design type; instead, they are a statistical method used to aggregate data sets from more than one study. They can be used for comparative study or systematic review study design types, but some people equate them solely to systematic reviews.

Narrative reviews, on the other hand, are an article type that provides a broad overview of a topic and often lacks the more rigorous features of a systematic review. Scoping reviews have increased in popularity in recent years but have a descriptive purpose that contrasts with systematic reviews. Sutton et al 121 have published an impressive inventory of the many types of reviews that might be confused with systematic reviews. The authors of systematic reviews themselves might contribute to the confusion by mislabeling these studies. The Library, Information Science, and Technology Abstracts database does not offer a filter for systematic reviews, so a keyword approach should be used when searching, followed by a manual screening of the resulting references.

Systematic reviews offer the potential to avoid many of the biases and pitfalls described at the beginning of this chapter.

In actuality, they can fall short of this potential to varying degrees, ranging from minor to monumental ways. The question being addressed needs to be narrowly focused to make the subsequent process manageable, which might disqualify some systematic reviews from application to HIPs’ actual EBP questions. The literature search might not be comprehensive, either due to limited sources searched or inadequately executed searches, leading to the possibility of missing important evidence. The searches might not be documented well enough to be reproduced by other researchers. The exclusion and inclusion criteria for identified studies might not calibrate with the needs of HIPs. The critical appraisal in some systematic reviews might exclude reviewed studies for trivial deficiencies or include studies with major flaws. The recommendations of some systematic reviews, therefore, might not be supported by the identified best available evidence.

Levels of Evidence

The Levels of Evidence, also known as “Hierarchies of Evidence,” are valuable sources of guidance in EBP. They serve as a reminder to busy practitioners that study designs at lower levels have difficulty in avoiding, controlling, or compensating for the many forms of bias or confounding that can affect research studies. Study designs at higher levels tend to be better at controlling biases. For example, higher-level study designs like RCTs can effectively control confounding. Table 8 organizes study designs according to EBP question type and arrays them into their approximate levels. In Table 8 , the “Intervention Question” column recognizes that a properly conducted systematic review incorporating multiple studies is generally more desirable for making an EBP decision compared to a case report. This is because the latter can be vulnerable to many forms of bias and confounding that rely on findings from a single instance. A systematic review, on the other hand, is ranked higher than even an RCT because it combines all available evidence from multiple studies and subjects them to a critical review, leading to a recommendation for making a decision.

Levels of Evidence: An Approximate Hierarchy Linked to Question Type

There are several important caveats to consider when using the Levels of Evidence. As noted earlier in this chapter, no perfect research study exists, and even higher-level of evidence research studies can have weaknesses. Hypothetically, an RCT could be so poorly executed that a well-conducted case report on the same topic could outshine it. While this is possible, it is highly unlikely due to the superior design of an RCT for controlling confounding or biases. Sometimes, a case report might be slightly more relevant than an RCT in answering an Intervention-type of EBP question. For these reasons, one cannot abandon their critical thinking skills even with a tacit acceptance of the Levels of Evidence.

The Levels of Evidence have been widely endorsed by HIP leaders for many years. 122 , 123 They undergo occasional adjustments, but their general organizing principles of controlling biases and other pitfalls remain intact. On balance, two of my otherwise respected colleagues have misinterpreted aspects of the early Levels of Evidence and made that the basis of their criticism. 124 , 125 A fair reading of the evolution of the Levels of Evidence over the years 126 , 127 , 128 , 129 should convince most readers that, when coupled with critical thinking, the underlying principles of the Levels of Evidence continue to provide HIPs with sound guidance.

Critical Appraisal Sheets

The critical appraisal sheets appended to this chapter are intended to serve as a guide for HIPs as they engage in critical appraisal of their potential evidence. The development of these sheets has been a culmination of over 20 years of effort. They draw upon my doctoral training in research methods, as well as my extensive experience conducting research using various study designs. Additionally, I have insights from multiple authorities. While it is impossible to credit all sources that have influenced the development of these sheets over the years, I have cited the readily recognized ones at the end of this sentence. 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141

• Critical Appraisal Worksheets

Appendix 1: Case Reports

Instructions: Answer the following questions to critically appraise this piece of evidence.

Appendix 2: Interviews

Appendix 3: descriptive surveys.

Instructions: Answer the following questions to critically appraise this piece of evidence

Appendix 4: Cohort Studies

Appendix 5: quasi-experiments, appendix 6: randomized controlled trials, appendix 7: systematic reviews.

This is an open access publication. Except where otherwise noted, this work is distributed under the terms of a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license (CC BY-NC-SA 4.0 DEED), a copy of which is available at https://creativecommons.org/licenses/by-nc-sa/4.0/ .

This open access peer-reviewed Book is brought to you at no cost to you by the Health Sciences Center at UNM Digital Repository. It has been accepted for inclusion in the Faculty Book Display Case by an authorized administrator of UNM Digital Repository. For more information, please contact [email protected].

• Cite this Page Eldredge J. Evidence Based Practice: A Decision-Making Guide for Health Information Professionals [Internet]. Albuquerque (NM): University of New Mexico Health Sciences Library and Informatics Center; 2024. Critical Appraisal.
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• Review Article
• Published: 20 January 2009

How to critically appraise an article

• Jane M Young 1 &
• Michael J Solomon 2  

Nature Clinical Practice Gastroenterology & Hepatology volume  6 ,  pages 82–91 ( 2009 ) Cite this article

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Critical appraisal is a systematic process used to identify the strengths and weaknesses of a research article in order to assess the usefulness and validity of research findings. The most important components of a critical appraisal are an evaluation of the appropriateness of the study design for the research question and a careful assessment of the key methodological features of this design. Other factors that also should be considered include the suitability of the statistical methods used and their subsequent interpretation, potential conflicts of interest and the relevance of the research to one's own practice. This Review presents a 10-step guide to critical appraisal that aims to assist clinicians to identify the most relevant high-quality studies available to guide their clinical practice.

Critical appraisal is a systematic process used to identify the strengths and weaknesses of a research article

Critical appraisal provides a basis for decisions on whether to use the results of a study in clinical practice

Different study designs are prone to various sources of systematic bias

Design-specific, critical-appraisal checklists are useful tools to help assess study quality

Assessments of other factors, including the importance of the research question, the appropriateness of statistical analysis, the legitimacy of conclusions and potential conflicts of interest are an important part of the critical appraisal process

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Making sense of the literature: an introduction to critical appraisal for the primary care practitioner

How to appraise the literature: basic principles for the busy clinician - part 2: systematic reviews and meta-analyses

How to appraise the literature: basic principles for the busy clinician - part 1: randomised controlled trials

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Critical Appraisal tools

Critical appraisal worksheets to help you appraise the reliability, importance and applicability of clinical evidence.

Critical appraisal is the systematic evaluation of clinical research papers in order to establish:

• Does this study address a  clearly focused question ?
• Did the study use valid methods to address this question?
• Are the valid results of this study important?
• Are these valid, important results applicable to my patient or population?

If the answer to any of these questions is “no”, you can save yourself the trouble of reading the rest of it.

This section contains useful tools and downloads for the critical appraisal of different types of medical evidence. Example appraisal sheets are provided together with several helpful examples.

Critical Appraisal Worksheets

• Systematic Reviews  Critical Appraisal Sheet
• Diagnostics  Critical Appraisal Sheet
• Prognosis  Critical Appraisal Sheet
• Randomised Controlled Trials  (RCT) Critical Appraisal Sheet
• Critical Appraisal of Qualitative Studies  Sheet
• IPD Review  Sheet

Chinese - translated by Chung-Han Yang and Shih-Chieh Shao

• Systematic Reviews  Critical Appraisal Sheet
• Diagnostic Study  Critical Appraisal Sheet
• Prognostic Critical Appraisal Sheet
• RCT  Critical Appraisal Sheet
• IPD reviews Critical Appraisal Sheet
• Qualitative Studies Critical Appraisal Sheet 

German - translated by Johannes Pohl and Martin Sadilek

• Systematic Review  Critical Appraisal Sheet
• Diagnosis Critical Appraisal Sheet
• Prognosis Critical Appraisal Sheet
• Therapy / RCT Critical Appraisal Sheet

Lithuanian - translated by Tumas Beinortas

• Systematic review appraisal Lithuanian (PDF)
• Diagnostic accuracy appraisal Lithuanian  (PDF)
• Prognostic study appraisal Lithuanian  (PDF)
• RCT appraisal sheets Lithuanian  (PDF)

Portugese - translated by Enderson Miranda, Rachel Riera and Luis Eduardo Fontes

• Portuguese – Systematic Review Study Appraisal Worksheet
• Portuguese – Diagnostic Study Appraisal Worksheet
• Portuguese – Prognostic Study Appraisal Worksheet
• Portuguese – RCT Study Appraisal Worksheet
• Portuguese – Systematic Review Evaluation of Individual Participant Data Worksheet
• Portuguese – Qualitative Studies Evaluation Worksheet

Spanish - translated by Ana Cristina Castro

• Systematic Review  (PDF)
• Diagnosis  (PDF)
• Prognosis  Spanish Translation (PDF)
• Therapy / RCT  Spanish Translation (PDF)

Persian - translated by Ahmad Sofi Mahmudi

• Prognosis  (PDF)
• PICO  Critical Appraisal Sheet (PDF)
• PICO Critical Appraisal Sheet (MS-Word)
• Educational Prescription  Critical Appraisal Sheet (PDF)

Explanations & Examples

• Pre-test probability
• SpPin and SnNout
• Likelihood Ratios

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Evidence appraisal: a scoping review, conceptual framework, and research agenda

Andrew goldstein, eric venker, chunhua weng.

• Author information
• Article notes
• Copyright and License information

Corresponding Author: Andrew Goldstein, 622 West 168th Street PH20, New York, NY 10032, USA. E-mail: [email protected] . Phone: +1 215-805-0082

Received 2016 Dec 23; Revised 2017 Mar 25; Accepted 2017 Apr 18; Issue date 2017 Nov.

Critical appraisal of clinical evidence promises to help prevent, detect, and address flaws related to study importance, ethics, validity, applicability, and reporting. These research issues are of growing concern. The purpose of this scoping review is to survey the current literature on evidence appraisal to develop a conceptual framework and an informatics research agenda.

We conducted an iterative literature search of Medline for discussion or research on the critical appraisal of clinical evidence. After title and abstract review, 121 articles were included in the analysis. We performed qualitative thematic analysis to describe the evidence appraisal architecture and its issues and opportunities. From this analysis, we derived a conceptual framework and an informatics research agenda.

We identified 68 themes in 10 categories. This analysis revealed that the practice of evidence appraisal is quite common but is rarely subjected to documentation, organization, validation, integration, or uptake. This is related to underdeveloped tools, scant incentives, and insufficient acquisition of appraisal data and transformation of the data into usable knowledge.

The gaps in acquiring appraisal data, transforming the data into actionable information and knowledge, and ensuring its dissemination and adoption can be addressed with proven informatics approaches.

Conclusions

Evidence appraisal faces several challenges, but implementing an informatics research agenda would likely help realize the potential of evidence appraisal for improving the rigor and value of clinical evidence.

Keywords: critical appraisal, post-publication peer review, journal clubs, journal comments, clinical research informatics

Background and Significance

Clinical research yields knowledge with immense downstream health benefits, 1–4 but individual studies may have significant flaws in their planning, conduct, analysis, or reporting, resulting in ethical violations, wasted scientific resources, and dissemination of misinformation, with subsequent health harm. 1 , 5–8 While much of the evidence base may be of high quality, individual studies may have issues, including nonalignment with knowledge gaps or health needs, neglect of prior research, 1 , 7 lack of biological plausibility, 9 miscalculation of statistical power, 10 , 11 poor randomization, low-quality blinding, 12 flawed selection of study participants or flawed outcome measures, 7 , 13–15 ethical misconduct during the trial (including issues with informed consent, 16 , 17 data fabrication, or data falsification), 18 , 19 flaws in statistical analysis, 20 nonreporting of research protocol changes, 7 outcome switching, 21 selective reporting of positive results, 5 plagiarized reporting, 19 , 22 misinterpretation of data, unjustified conclusions, 23 , 24 and publication biases toward statistical significance and newsworthiness. 7

In order to prevent, detect, and address these issues, several mechanisms exist or have been promoted, including reforming incentives for research funding, publication, and career promotion 1 , 5–8 , 25 ; preregistering trial protocols 5 , 26–28 ; sharing patient-level trial data 5 , 23 , 29–31 ; changing journal-based pre-publication peer review 32 , 33 ; performing meta-research 34 , 35 ; performing risk of bias assessment as part of meta-analysis, systematic review, and development of guidelines and policies 23 , 36–38 ; and expanding reproducibility work via data reanalysis 39 and replication studies. 40 However, despite these measures, the published literature often lacks value, rigor, and appropriate interpretation. This is occurring during a period of growth in the published literature, leading to information overload. 41–43 Further, there is a large volume of nontraditional and emerging sources of evidence: results, analyses, and conclusions outside of the scientific peer-reviewed literature, including via trial registries and data repositories, 26 , 27 , 44 , 45 observational datasets, 46 , 47 publication without journal-based peer review, 48–50 and scientific blogging. 51–53

Here, therefore, we discuss evidence appraisal. This refers to the critical appraisal of published clinical studies via evaluation and interpretation by informed stakeholders, and is also called trial evaluation, critical appraisal, and post-publication peer review (PPPR). Evidence appraisal has generated considerable interest, 23 , 48 , 54–64 and a significant volume of appraisal is already occurring with academic journal clubs, published journal comments (eg, PubMed has more than 55 000 indexed clinical trials that have 1 or more journal comments), PPPR platforms, social media commentary, and trial risk of bias assessment as part of evidence synthesis.

While evidence appraisal is prevalent, downstream use of its generated knowledge is underdefined and underrealized. We believe evidence appraisal addresses many important needs of the research enterprise. It is key to bridging the T2 phase (clinical research or translation to patients) and T3 phase (implementation or translation to practice) of translational research by ensuring appropriate dissemination and uptake (including implementation and future research planning). 65 Further, appraisal of evidence by patients, practitioners, policy-makers, and researchers enables informed stakeholder feedback and consensus-making as part of both learning health system 66–68 and patient-centered outcomes research 69–71 paradigms, and can help lead to research that better meets health needs. As appraisal of evidence can help determine research quality and appropriate interpretation, this process is also aligned with recent calls to improve the rigor, reproducibility, and transparency of published science. 72–74 Evidence appraisal knowledge can be envisioned, therefore, to enable a closed feedback loop that clarifies primary research and enables better interpretation of the evidence base, detection of research flaws, application of evidence in practice and policy settings, and alignment of future research with health needs.

Despite these benefits, the field of evidence appraisal is undefined and understudied. Though there is some siloed literature on journal commentary, journal clubs, and online PPPR (which we review and describe here), the broader topic of evidence appraisal, especially the uptake of knowledge emerging from this process, is unexplored and we find no reviews, conceptual frameworks, or research agendas for this important field.

In this context, our goals are to address these knowledge gaps by better characterizing evidence appraisal and proposing a systematic framework for it, as well as to raise awareness of this important but neglected step in the evidence lifecycle and component of the research system. We also seek to identify opportunities to increase the scale, rigor, and value of appraisal. Specifically, informatics is enabling transformative improvement of information and knowledge management involving the application of large, open datasets, social computing platforms, and automation tools, which could similarly be leveraged to enhance evidence appraisal.

Therefore, we performed a scoping review of post-publication evidence appraisal within the biomedical literature and describe its process architecture, appraisers, use cases, issues, and informatics opportunities. Our ultimate goal was to develop a conceptual framework and propose an informatics research agenda by identifying high-value opportunities to advance research in systematic evidence appraisal and improve appropriate evidence utilization throughout the translational research lifecycle.

Materials and Methods

We conducted a scoping review, including a thematic analysis. Our methodology was adapted from Arksey and O’Malley, with changes allowing for broader inclusion, iterative analysis, and more efficient implementation. 75 This method involves 3 steps: (1) identifying potential studies, (2) screening studies for inclusion, and (3) conducting thematic analysis, with collation and reporting of the findings.

Article search

To identify potential studies in the biomedical literature, we searched for any citation in Medline published by the time of our search, December 6, 2015. Our search prioritized precision while maintaining temporal comprehensiveness at the cost of recall via more comprehensive search terms. This search strategy placed emphasis on specific search terms that were more likely to identify articles relevant to evidence appraisal ( Supplementary Appendix 1A ). Search terms related to appraisal included PPPR, journal club, and the evaluation, assessment, or appraisal of studies, trials, or evidence. We used this narrower set of search terms in 1 citation database (Medline). Our initial search yielded 2187 citations. During screening and thematic analysis, further search terms were identified (Appendix 1B), yielding another 237 citations. Of these 2424 citations, there were 2422 unique articles.

Article screening

One researcher (AG) manually screened the titles and abstracts of all retrieved articles. Articles were included if they contained discussion of the post-publication appraisal processes, challenges, or opportunities for evidence that was either in science or biomedicine generally or specific to health interventions. Articles were excluded if they did not meet those criteria or were instances of evidence appraisal (eg, the publication of proceedings from a journal club) or discussed evidence appraisal as part of pre-publication review, meta-research, meta-analysis, or systematic review. Citations were included regardless of article type (eg, studies, reviews, announcements, and commentary). Non-English articles were excluded. Ultimately, this led to a total of 121 articles meeting the criteria for thematic analysis. The search and screening Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram 76 is shown in Figure 1 .

Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram demonstrating article screening process. ( A ) During article screening and initial thematic analysis, additional search terms were identified and a further search was performed. ( B ) Screening was performed on the title and, as available, the abstract of retrieved articles, with full text reviewed if available and further ambiguity remained.

Thematic analysis

Two reviewers (AG and EV) extracted themes manually from the full-text article or, if this was unavailable, from the abstract. Thematic analysis involved iterative development of the coding scheme and iterative addition of search terms for identifying new articles. The coding scheme was updated based on discussions and consensus of both reviewers, followed by reassessment of previously coded articles for the new codes. Coding was validated with discrepancies adjudicated by discussion until consistency and consensus were achieved. Final themes were then grouped into categories. These themes and categories were then used to develop a de novo conceptual framework by author consensus.

Descriptive statistics

The 121 articles included in this review were published in 90 unique journals, with each journal on average having 1.34 articles included in the study (standard deviation 1.00). The maximum number of articles from a single journal ( Frontiers in Computational Neuroscience ) was 9. There were 4 articles from the Journal of Evaluation in Clinical Practice , and 3 each from BMC Medical Education , Clinical Orthopedics and Related Research , the Journal of Medical Internet Research , and Medical Teacher. The number of articles published by year is found in Figure 2 . We were able to access the full text for 119 articles and used only the abstract for the remaining 2.

Number of articles by publication year.

The articles spanned a range of publication types: 24 reviews, 18 trials, 3 observational studies, 21 surveys, 44 editorials and perspectives, 7 comments and letters to the editor, and 4 journal announcements ( Figure 3 ).

Number of articles by publication type.

Sixty-eight distinct themes forming 10 categories (A–J) were identified from these 121 articles. An average of 7.16 themes were found in each article (standard deviation 3.44). Themes occurred 866 times in total, with a mean of 12.55 instances per theme (standard deviation 15.71). The themes, theme categories, and articles in which themes were identified are provided in Table 1 and described below.

Themes are listed with theme codes in parentheses; the first letter is the major theme category it is a part of, followed by additional categories it is a member of. For example, theme 1 is primarily in category A but also in category D. Theme category key: A = Initiation Promoters; B = Initiation Inhibitors; C = Article Selection Sources; D = Appraiser Characteristics; E = Tools and Methods; F = Appraisal Venue; G = Format Characteristics; H = Appraisal Process Issues; I = Post-Appraisal Publication, Organization, and Use; J = Post-Appraisal Issues and Concerns. EQUATOR = Enhancing the Quality and Transparency of Health Research; JAMA  =  Journal of the American Medical Association

Category A: Appraisal initiation promoters

Many articles discussed why appraisal was or was not initiated (category A). Appraisal is often required for student coursework (theme 1), required or encouraged for continuing education (theme 2), or performed to answer evidentiary questions at the point of practice (theme 3), including clinical practice, program development, and policymaking. These themes were frequently discussed related to a broader theme of evidence-based practice. Most of these instances were appraiser-centric in that they were focused on the appraisal process benefiting the practitioner’s ability to perform daily tasks via a better personal critical understanding of the evidence.

In contrast to appraiser-centric appraisal as part of improving appropriate evidence application, a significant share of appraisal was motivated by the goal of improving the rigor of scientific evidence and its interpretation (theme 4) and was more commonly focused on the research system. These articles highlighted fields of open science, such as open-access publishing and open evaluation. As some open-access publications do not undergo pre-publication peer review, post-publication peer review was described as the only review process for these articles (theme 5).

When appraisal happens, certain attributes of the process are perceived to motivate increases in the scale or quality of appraisal. Some meetings, such as journal clubs, are scheduled regularly, which serves to both enhance attendance and develop institutional culture and habits of evidence appraisal (theme 6). Meetings being mandatory (theme 7) was discussed in conflicting ways. By some, mandatory sessions were considered to increase attendance, and thus the scale and richness of group discussion, but one article described voluntary attendance as preferred, as participants are more self-motivated to attend and more likely to participate. Social status incentives for appraising or for appraising with high quality, as well as research career incentives via academic rewards for appraisals, were described as potentially increasing participation (theme 8). Various other incentives that increase participation were also mentioned (theme 9), including offering continuing education credits, providing food, providing time for socializing, meeting local institutional requirements for work or training, and offering unspecified incentives.

Category B: Appraisal initiation inhibitors

Articles also described several inhibitors of appraisal initiation (category B). The most commonly cited inhibitor was the time burden to perform evidence appraisal and the time requirements for other work (theme 10). One result of this is that when appraised evidence is demanded, some practitioners will utilize or rely on previous appraisals made by others rather than producing their own (theme 11). Other inhibitors of appraisal include lack of access to full-text articles (theme 12) and lack of explicit funding support for performing appraisal (theme 13).

Category C: Article selection sources

There are many rationales for or contexts in which an article might be appraised (category C). Typically, selection is task-dependent related to learning, practice, or specific research needs. For initial learning in a field, landmark studies (theme 14), also called classic, seminal, or practice-changing studies, were selected for their historical value in helping learners understand current practices and field-specific trends in research. For continuing education, articles were selected for appraisal based on recently published articles (theme 15) or from recent clinical questions (theme 16). A novel approach to article selection for continuing education was discussed: collaborative filtering or recommendation systems (theme 17), which provide a feed of content to users based on their interests or on prior evidence reviewed. For skills development–oriented appraisal, selection of studies also aligned with classic, recent, or practice question–driven study selection. Of note, very frequently no rationale for article selection was explicitly stated.

Category D: Common and innovative appraiser characteristics

Appraisers had varied characteristics (category D). It is implicit in many themes that appraisal stakeholders include researchers and practitioners, at the student (theme 1) as well as training and post-training levels (themes 2 and 3). The stakeholders involved in a given appraisal setting were typically a relatively homogenous group of practitioners at a similar stage of training and in silos by field. However, other appraisers or groups with innovative characteristics have also been engaged and warranted thematic analysis.

Rarely, appraisal included or was suggested to include laypeople, such as patients, study participants, or the general public (theme 18). Some groups performing appraisal were multidisciplinary and included different types of health professionals or methodologists, including librarians and those with expertise in epidemiology or biostatistics (theme 19).

For post-publication peer-review platforms, disclosure of the identity of appraisers was a common yet controversial topic. There were rationales advocating for and against, and examples of anonymous, pseudonymous, and named authorship of appraisals (theme 20). The motivating factor for this was optimizing who decides to initiate, what and how they critique, how they express and publish it, and how the appraisal is received by readers.

Regarding appraiser attributes, only one significant issue was raised: individual appraiser quality and subsequent inter-appraiser unreliability (theme 51).

Category E: Appraisal tools and methods

There are many tools for appraisal (category E), mostly to support humans performing appraisal. Most evidence appraisal tools were specifically developed for other purposes, including clinical practice guideline development (theme 21), systematic review production (themes 22 and 23), and trial-reporting checklists (theme 24). Some were based on frameworks for evidence-based practice (themes 25–27), which focus on trial design and interpretation evaluation to assess validity and applicability. Several articles mentioned unspecified structured tools, including homegrown tools, or use of an unspecified journal club approach (themes 28 and 29).

Tools were frequently referenced as potential methods for appraisal or as specifically used in studies and reviews of appraisal venues, such as journal clubs. Dimensions of appraisal were not frequently specified, but when they were, they typically focused on evidence validity and, to a lesser degree, applicability and reporting. No dimension focused on biological plausibility, ethics, or importance. In fact, these missing dimensions were highlighted as an important issue facing appraisal tools (theme 52). Similarly, it was discussed that there is a need for tailored tools for specific fields, problems, interventions, study designs, and outcomes (theme 53).

These structured, multidimensional tools were common for journal clubs. Many articles discussing settings other than journal clubs did not describe the use of tools. Some, however, proposed or described other approaches, including global ratings, such as simple numerical scores that are averages of subjective numerical user ratings (theme 30). Other ratings included automatically generated ones, such as journal impact factors (theme 31) and novel computational approaches aimed at identifying fraud (theme 32).

Category F: Appraisal venues

Appraisal of evidence occurs in a wide range of venues (category F). In-person group meetings as part of courses or journal clubs was the most common venue in our review (theme 33). Online forums were also common, specifically as a means for either performing a journal club as part of evidence-based practice or performing appraisal as part of the drive for more rigorous science (themes 34–38). Less commonly discussed were journal comments (theme 39) and simply reviewing the literature on one’s own, outside of any specific setting (theme 40). Most unique was an institution’s professional service that performed appraisal to answer evidentiary questions (theme 41).

Category G: Appraisal format

Regardless of the domains discussed or tools used, the appraisal process occurred in varied formats (category G). Journal clubs and course meetings were the most common, and were typically presentations or discussions attended synchronously by all attendees (theme 33). Many discussions were facilitated or moderated by either the presenter or another individual (theme 42). Less commonly, there were innovative formats, including debates (theme 43) and an approach that we call “generative-comparative,” whereby participants were prompted by the study question to propose an ideal study design to answer the question and to which they compared the actual study design (theme 44).

Online settings offered different approaches. Online journal clubs were typically asynchronous discussions where participants could comment at their convenience (theme 38). Several online platforms allow for indefinite posting, thereby enabling additional appraisals as information and contexts change (theme 45). Most online platforms utilized threaded comments (themes 35 and 37) or isolated comments (themes 34 and 36); however, online collaborative editing tools were also discussed as a format (theme 46).

Category H: Appraisal process issues

Several notable issues and concerns about the appraisal process were raised in the literature (category H). Some articles expressed concern surrounding the possibility that appraisers, in an effort to not offend or affect future funding or publishing decisions, might be overly positive in their conclusions (theme 47). Conversely, some authors were concerned that appraisers, especially those in anonymous or online settings, might be more likely to state only negative criticisms (theme 47) or be uncivil (theme 48). Another concern was that appraisal, especially in open, anonymous forums, would result in comments that were of lower quality compared with those garnered by other venues, where appraisers might have more expertise or be more thoughtful (theme 49). Lastly, despite the potential benefits of novel online appraisal platforms, it was frequently mentioned that many of these tools are actually quite underused (theme 50).

Category I: Post-appraisal publication, organization, and use

After appraisal is performed, much can occur, or not, with the information generated (category I). Many articles discussing appraisal either specifically highlighted that the appraisal went unrecorded (theme 54) or did not specifically mention any recording, publication, or use outside of any learning that the appraiser experienced. Several studies did report that the appraisal content was recorded and locally published or stored for future local retrieval but not widely disseminated (theme 55).

When appraisals were disseminated, they were published either immediately online (theme 56) or within a journal (theme 57). Indexing or global aggregation of published appraisals was occasionally discussed (theme 58). Journal-based publications are automatically indexed within Medline; however, there was also discussion of indexing nonjournal published appraisals, though these discussions were theoretical. There was limited discussion of data standards (theme 59) and linkage to primary articles (theme 60).

There was some discussion about automatic responses to appraisals that are published. This included evaluating the quality of the appraisal (theme 61), messaging the appraisal to the authors of the original article (theme 62), having journal editors issue any needed corrections or retractions (theme 63), and having functionality for integrating appraisals related to a specific or set of dimensions (eg, research question, article author, appraiser, study design characteristic) (theme 64).

Category J: Post-appraisal concerns

Several issues were raised regarding appraisal data after publication (category J). Specifically, there were concerns that the volume of appraisals would worsen information overload (theme 65). Related to this concern is managing redundant appraisals (theme 66). Additionally, several articles highlighted the low quality of research on evidence appraisal (theme 67), particularly for journal clubs, where most of the research has been performed, as well as the low volume of research for both journal club and other formats of appraisal. Even when appraisals are documented, published, and accessible, they are underused (theme 68).

In sum, our scoping review demonstrates that evidence appraisal is occurring in a variety of different contexts (category F), by various stakeholders (category D), and to address a wide range of questions (themes 1–3 and 16). This appraisal occurs with varied tools (category E), formats (categories F and G), and approaches to dissemination (category I). Appraisal is insufficiently supported (themes 10 and 13) and researched (theme 67), lacks crucial infrastructure (themes 58–60), and is minimally applied (theme 68).

A conceptual framework

From our thematic analysis, we derived a conceptual framework for evidence appraisal ( Figure 4 ). This was developed by first integrating emergent concepts related to evidence-appraisal processes and resources from the themes and theme categories, as well as domain knowledge in informatics. This was performed via iterative, consensus-driven discussion by the authors. Formal quantification of the significance and prevalence of these processes and resources is not within the scope of this review, but general levels of existence or gaps have been provided to the best of our knowledge as a result of performing this review and from our knowledge of relevant informatics resources.

Conceptual framework. This figure illustrates the architecture of evidence appraisal as described or discussed in the biomedical literature and with actual or potential informatics resources to enable key steps. Superscript includes relevant themes or theme categories. The line style indicates whether these elements were described to exist or not within the scoping review or to the authors’ knowledge.

Evidence appraisal is typically driven by a specific rationale, often related to a task, an institutional or professional requirement, or broader motivations, to ensure scientific rigor or pursue lifelong learning. Once convened, appraisal has several attributes. One attribute is the stage of the evidence’s lifecycle. Appraisal can occur at the protocol stage, near the time of publication, or long after publication, when further contextual information is available, such as new standards of care or the identification of new adverse effects. Appraisal is also influenced by appraiser characteristics, tools used, venue, and format.

Once evidence has been appraised, the data from this appraisal instance can then be acquired as part of documentation or publication. The data can conform to data standards, and its capture can be aided by specific platforms or tools. The data can subsequently be mapped to an ontology, be indexed, or be curated and managed in other ways to improve data use. These processes help characterize and contextualize the data, essentially rendering it as information. This information can then be validated, integrated, and visualized, allowing for ultimate appraisal knowledge uptake as part of use cases. These use cases may include evidence synthesis, meta-research, scientific integrity assurance, methods development, determination of potential research questions, determination of research priorities, enabling of practice and policy decision-making, integration into education and training curricula, public science communication, and patient engagement. Our scoping review shows that this transformation from unrecorded content to actionable information and knowledge is underrealized.

Gaps and opportunities facing evidence appraisal

Research in this area is notably limited. No prior reviews of this topic have been performed. While there is significant research regarding journal clubs and PPPR, it is mainly descriptive and the trials were described as low quality. There are no Medical Subject Headings terms in PubMed for this field.

Our scoping review demonstrates that evidence appraisal faces significant challenges with data acquisition, management, organization, quality, coverage, availability, usability, and use. Underlying these issues is the lack of a significant organized field for evidence appraisal, and, as such, there is only minimal work to develop knowledge representation schemes, data standards, automatic knowledge acquisition or synthesis tools, and a central, aggregated, accessible, usable database for evidence appraisals. This has direct implications for data organization and usability, and may limit upstream data acquisition and coverage and downstream analysis and use. Enabling the transformation of appraisals from undocumented content to usable knowledge will require development of knowledge and technology tools, such as data standards, documentation tools, repositories, ontology, annotation tools, retrieval tools, validation systems, and integration and visualization systems.

While journal clubs appear to be ubiquitous, especially for medical trainees, they are learner-centric and lack data acquisition, limiting reuse of the appraisal content generated during discussions. Meanwhile, PPPR platforms, collaborative editing tools, and social media are increasingly discussed but appear to face underuse, fragmentation, and a lack of standardization. This discrepancy in appraisal production and use of data acquisition tools leads to downstream data issues. But this large volume of undocumented appraisals also reflects an opportunity, as appraisal production is already occurring at scale and only requires mechanisms and norms for data acquisition.

It is worth noting the rarity and absence of certain themes. There was little discussion of researchers or post-training practitioners performing journal clubs or of appraisal at academic conferences. There was little discussion of journal commentary, its evaluation, or the access barriers facing it. There was no discussion of developing approaches for lay stakeholders, such as patients and study participants, to appraise evidence, specifically related to study importance, ethical concerns, patient-centered outcome selection, or applicability factors.

Most important, there was minimal discussion regarding the establishment of a closed feedback loop whereby appraisals are not just generated by the research system, but are also utilized by it. Specifically, the research system could potentially utilize appraisal knowledge to improve public science communication, research prioritization, methods development, core outcome set determination, research synthesis, guideline development, and meta-research. Underlying the gap in appraisal uptake is the absence of institutions, working groups, and research funding mechanisms related to appraisal generation, processing, and dissemination.

An informatics research agenda

The key gaps facing evidence appraisal are related to increasing and improving the generation, acquisition, organization, integration, retrieval, and uptake of a large volume of appraisal data, which frequently involves complex natural language. Therefore, the evidence appraisal field would be best served by intensive research by the informatics community. Accordingly, we propose a specific research agenda informed by the knowledge of gaps identified in this review ( Table 2 ). This agenda primarily focuses on related informatics methodology research, with novel application to the evidence appraisal domain. The agenda begins with enhancing appraisal data acquisition, organization, and integration by addressing gaps identified in the thematic analysis and conceptual framework, particularly the lack of engagement tools, documentation tools, standards, aggregation, and repositories. This is to be accomplished via dataset aggregation, novel data production (including automated approaches), acquisition of data from current areas without documentation (eg, journal clubs), and development of data standards.

Next, we propose developing and applying an ontology for appraisal concepts and for data-quality and validity research. As noted in the conceptual framework, this area is, to our knowledge, nonexistent. Next, we propose developing tools and platforms that enable retrieval, recommendation, and visualization to enable appraisal knowledge application, which, again, is minimally existent outside of the task for which the appraisal was initially performed. Examples of potential appraisal concepts could include “trial arms lack equipoise,” “outcomes missing key patient-centered quality of life measure,” and “reported primary outcome is discrepant with the primary outcome described in the protocol.”

This will enable the next areas of research we propose, which also address the gap of adopting or applying appraisal knowledge: first, primary evidence appraisal knowledge research – descriptive, association-focused, and intervention research on appraisal information and knowledge resources; and second, use of appraisal information and knowledge to improve other translational research tasks via applied research. Primary appraisal research will include studying and developing appraisal methods, understanding relationships between clinical research and the appraisal of clinical research, and understanding relationships between appraisal data and scientific outcomes, such as representativeness, media sensationalization of science, science integrity issue detection, publication retraction, and clinical standard of care change. Enabled translational research uses of appraisal knowledge include integration during evidence synthesis, future study planning and prioritization, performance of meta-research, and the application of appraisal to emerging and nontraditional sources of evidence, such as trial results in registries and repositories, journal articles lacking peer review, and analyses and conclusions in scientific blogging.

Lastly, sociotechnical work is an important component of our agenda. We propose that an evidence appraisal working group convene to better approach the aforementioned research, to promote funding and incentive changes, and to change cultural norms regarding the production and uptake of appraisal knowledge.

Limitations

This was a focused search that excluded synthesis tasks that might include appraisal components, did not perform snowball sampling, and had limited search terms due to high false positive rates. This approach allowed for feasible research with increased efficiency, but compromised the exhaustiveness of our results. Given our very broad research question and preference to include scientific discourse from other time periods, this was considered the most optimal approach. These limitations may affect references and themes identified. However, the goal of this review was not to conduct an exhaustive search or analysis, and was instead aimed at capturing common and emerging themes. Thematic analysis is inherently subjective, and other investigators may have arrived at different themes. Though it may be subject to these biases, this review was based on an open, iterative discourse to identify, modify, and ascribe themes.

ConclusionS

While evidence appraisal has existed in a variety of forms for decades and has immense potential for enabling higher-value clinical research, it faces myriad obstacles. The field is fragmented, undefined, and underresearched. Data from appraisal are rarely captured, organized, and transformed into usable knowledge. Appraisal knowledge is underutilized at other steps in the translational science pipeline. The evidence appraisal field lacks key research, infrastructure, and incentives. Despite these issues, discussion of appraisal is on the rise, and novel tools and data sources are emerging. We believe our proposed informatics research agenda provides a potential path forward to solidify and realize the potential of this emerging field.

Supplementary Material

Acknowledgments.

This work was supported by R01 LM009886 (Bridging the Semantic Gap between Research Eligibility Criteria and Clinical Data; principal investigator, CW) and T15 LM007079 (Training in Biomedical Informatics at Columbia; principal investigator, Hripcsak).

Contributors

AG proposed the methods, completed search and screening, performed thematic analysis, and drafted the manuscript. EV performed thematic analysis and contributed to the conceptual framework development and manuscript drafting. CW supervised the research, participated in study design, and edited the manuscript.

Competing interests

Supplementary material.

Supplementary material is available at Journal of the American Medical Informatics Association online.

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Critical Appraisal: A Checklist

Posted on 6th September 2016 by Robert Will

Critical appraisal of scientific literature is a necessary skill for healthcare students. Students can be overwhelmed by the vastness of search results. Database searching is a skill in itself, but will not be covered in this blog. This blog assumes that you have found a relevant journal article to answer a clinical question. After selecting an article, you must be able to sit with the article and critically appraise it. Critical appraisal of a journal article is a literary and scientific systematic dissection in an attempt to assign merit to the conclusions of an article. Ideally, an article will be able to undergo scrutiny and retain its findings as valid.

The specific questions used to assess validity change slightly with different study designs and article types. However, in an attempt to provide a generalized checklist, no specific subtype of article has been chosen. Rather, the 20 questions below should be used as a quick reference to appraise any journal article. The first four checklist questions should be answered “Yes.” If any of the four questions are answered “no,” then you should return to your search and attempt to find an article that will meet these criteria.

Critical appraisal of…the Introduction

• Does the article attempt to answer the same question as your clinical question?
• Is the article recently published (within 5 years) or is it seminal (i.e. an earlier article but which has strongly influenced later developments)?
• Is the journal peer-reviewed?
• Do the authors present a hypothesis?

Critical appraisal of…the Methods

• Is the study design valid for your question?
• Are both inclusion and exclusion criteria described?
• Is there an attempt to limit bias in the selection of participant groups?
• Are there methodological protocols (i.e. blinding) used to limit other possible bias?
• Do the research methods limit the influence of confounding variables?
• Are the outcome measures valid for the health condition you are researching?

Critical appraisal of…the Results

• Is there a table that describes the subjects’ demographics?
• Are the baseline demographics between groups similar?
• Are the subjects generalizable to your patient?
• Are the statistical tests appropriate for the study design and clinical question?
• Are the results presented within the paper?
• Are the results statistically significant and how large is the difference between groups?
• Is there evidence of significance fishing (i.e. changing statistical tests to ensure significance)?

Critical appraisal of…the Discussion/Conclusion

• Do the authors attempt to contextualise non-significant data in an attempt to portray significance? (e.g. talking about findings which had a  trend  towards significance as if they were significant).
• Do the authors acknowledge limitations in the article?
• Are there any conflicts of interests noted?

This is by no means a comprehensive checklist of how to critically appraise a scientific journal article. However, by answering the previous 20 questions based on a detailed reading of an article, you can appraise most articles for their merit, and thus determine whether the results are valid. I have attempted to list the questions based on the sections most commonly present in a journal article, starting at the introduction and progressing to the conclusion. I believe some of these items are weighted heavier than others (i.e. methodological questions vs journal reputation). However, without taking this list through rigorous testing, I cannot assign a weight to them. Maybe one day, you will be able to critically appraise my future paper:  How Online Checklists Influence Healthcare Students’ Ability to Critically Appraise Journal Articles.

Feature Image by Arek Socha from Pixabay

Robert Will

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No Comments on Critical Appraisal: A Checklist

Hi Ella, I have found a checklist here for before and after study design: https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools and you may also find a checklist from this blog, which has a huge number of tools listed: https://s4be.cochrane.org/blog/2018/01/12/appraising-the-appraisal/

What kind of critical appraisal tool can be used for before and after study design article? Thanks

Hello, I am currently writing a book chapter on critical appraisal skills. This chapter is limited to 1000 words so your simple 20 questions framework would be the perfect format to cite within this text. May I please have your permission to use your checklist with full acknowledgement given to you as author? Many thanks

Thank you Robert, I came across your checklist via the Royal College of Surgeons of England website; https://www.rcseng.ac.uk/library-and-publications/library/blog/dissecting-the-literature-the-importance-of-critical-appraisal/ . I really liked it and I have made reference to it for our students. I really appreciate your checklist and it is still current, thank you.

Hi Kirsten. Thank you so much for letting us know that Robert’s checklist has been used in that article – that’s so good to see. If any of your students have any comments about the blog, then do let us know. If you also note any topics that you would like to see on the website, then we can add this to the list of suggested blogs for students to write about. Thank you again. Emma.

i am really happy with it. thank you very much

A really useful guide for helping you ask questions about the studies you are reviewing BRAVO

Dr.Suryanujella,

Thank you for the comment. I’m glad you find it helpful.

Feel free to use the checklist. S4BE asks that you cite the page when you use it.

I have read your article and found it very useful , crisp with all relevant information.I would like to use it in my presentation with your permission

That’s great thank you very much. I will definitely give that a go.

I find the MEAL writing approach very versatile. You can use it to plan the entire paper and each paragraph within the paper. There are a lot of helpful MEAL resources online. But understanding the acronym can get you started.

M-Main Idea (What are you arguing?) E-Evidence (What does the literature say?) A-Analysis (Why does the literature matter to your argument?) L-Link (Transition to next paragraph or section)

I hope that is somewhat helpful. -Robert

Hi, I am a university student at Portsmouth University, UK. I understand the premise of a critical appraisal however I am unsure how to structure an essay critically appraising a paper. Do you have any pointers to help me get started?

Thank you. I’m glad that you find this helpful.

Very informative & to the point for all medical students

How can I know what is the name of this checklist or tool?

This is a checklist that the author, Robert Will, has designed himself.

Thank you for asking. I am glad you found it helpful. As Emma said, please cite the source when you use it.

Greetings Robert, I am a postgraduate student at QMUL in the UK and I have just read this comprehensive critical appraisal checklist of your. I really appreciate you. if I may ask, can I have it downloaded?

Please feel free to use the information from this blog – if you could please cite the source then that would be much appreciated.

Robert Thank you for your comptrehensive account of critical appraisal. I have just completed a teaching module on critical appraisal as part of a four module Evidence Based Medicine programme for undergraduate Meducal students at RCSI Perdana medical school in Malaysia. If you are agreeable I would like to cite it as a reference in our module.

Anthony, Please feel free to cite my checklist. Thank you for asking. I hope that your students find it helpful. They should also browse around S4BE. There are numerous other helpful articles on this site.

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