1 Yay! Welcome!
2 A journal club is when a group of scientists get together to discuss a paper. Usually one person leads the discussion and presents all of the data. The group discusses their own interpretations and the authors’ interpretation.
In written communication, the reader and the writer are equally important. Both influence the final outcome: in this case, your scientific understanding! After identifying your goal, think about the author’s goal for sharing this project. This will help you interpret the data and understand the author’s interpretation of the data. However, this requires some understanding of who the author(s) are (e.g., what are their scientific interests?), the scientific field in which they work (e.g., what techniques are available in this field?), and how this paper fits into the author’s research (e.g., is this work building on an author’s longstanding project or controversial idea?). This information may be hard to glean without experience and a history of reading. But don’t let this be a discouragement to starting the process; it is by the act of reading that this experience is gained!
A good step toward understanding the goal of the author(s) is to ask yourself: What kind of article is this? Journals publish different types of articles, including methods, review, commentary, resources, and research articles as well as other types that are specific to a particular journal or groups of journals. These article types have different formatting requirements and expectations for content. Knowing the article type will help guide your evaluation of the information presented. Is the article a methods paper, presenting a new technique? Is the article a review article, intended to summarize a field or problem? Is it a commentary, intended to take a stand on a controversy or give a big picture perspective on a problem? Is it a resource article, presenting a new tool or data set for others to use? Is it a research article, written to present new data and the authors’ interpretation of those data? The type of paper, and its intended purpose, will get you on your way to understanding the author’s goal.
When reading, ask yourself: (1) What do the author(s) want to know (motivation)? (2) What did they do (approach/methods)? (3) Why was it done that way (context within the field)? (4) What do the results show (figures and data tables)? (5) How did the author(s) interpret the results (interpretation/discussion)? (6) What should be done next? (Regarding this last question, the author(s) may provide some suggestions in the discussion, but the key is to ask yourself what you think should come next.)
Each of these questions can and should be asked about the complete work as well as each table, figure, or experiment within the paper. Early on, it can take a long time to read one article front to back, and this can be intimidating. Break down your understanding of each section of the work with these questions to make the effort more manageable.
Scientists write original research papers primarily to present new data that may change or reinforce the collective knowledge of a field. Therefore, the most important parts of this type of scientific paper are the data. Some people like to scrutinize the figures and tables (including legends) before reading any of the “main text”: because all of the important information should be obtained through the data. Others prefer to read through the results section while sequentially examining the figures and tables as they are addressed in the text. There is no correct or incorrect approach: Try both to see what works best for you. The key is making sure that one understands the presented data and how it was obtained.
For each figure, work to understand each x- and y-axes, color scheme, statistical approach (if one was used), and why the particular plotting approach was used. For each table, identify what experimental groups and variables are presented. Identify what is shown and how the data were collected. This is typically summarized in the legend or caption but often requires digging deeper into the methods: Do not be afraid to refer back to the methods section frequently to ensure a full understanding of how the presented data were obtained. Again, ask the questions in Rule 3 for each figure or panel and conclude with articulating the “take home” message.
Just like the overall intent of the article (discussed in Rule 2), the intent of each section within a research article can guide your interpretation. Some sections are intended to be written as objective descriptions of the data (i.e., the Results section), whereas other sections are intended to present the author’s interpretation of the data. Remember though that even “objective” sections are written by and, therefore, influenced by the authors interpretations. Check out Table 2 to understand the intent of each section of a research article. When reading a specific paper, you can also refer to the journal’s website to understand the formatting intentions. The “For Authors” section of a website will have some nitty gritty information that is less relevant for the reader (like word counts) but will also summarize what the journal editors expect in each section. This will help to familiarize you with the goal of each article section.
Section | Content |
---|---|
Title | The “take home” message of the entire project, according to the authors. |
Author list | These people made significant scientific contributions to the project. Fields differ in the standard practice for ordering authors. For example, as a general rule for biomedical sciences, the first author led the project’s implementation, and the last author was the primary supervisor to the project. |
Abstract | A brief overview of the research question, approach, results, and interpretation. This is the road map or elevator pitch for an article. |
Introduction | Several paragraphs (or less) to present the research question and why it is important. A newcomer to the field should get a crash course in the field from this section. |
Methods | What was done? How was it done? Ideally, one should be able to recreate a project by reading the methods. In reality, the methods are often overly condensed. Sometimes greater detail is provided within a “Supplemental” section available online (see below). |
Results | What was found? Paragraphs often begin with a statement like this: “To do X, we used approach Y to measure Z.” The results should be objective observations. |
Figures, tables, legends, and captions | The data are presented in figures and tables. Legends and captions provide necessary information like abbreviations, summaries of methods, and clarifications. |
Discussion | What do the results mean and how do they relate to previous findings in the literature? This is the perspective of the author(s) on the results and their ideas on what might be appropriate next steps. Often it may describe some (often not all!) strengths and limitations of the study: Pay attention to this self-reflection of the author(s) and consider whether you agree or would add to their ideas. |
Conclusion | A brief summary of the implications of the results. |
References | A list of previously published papers, datasets, or databases that were essential for the implementation of this project or interpretation of data. This section may be a valuable resource listing important papers within the field that are worth reading as well. |
Supplemental material | Any additional methods, results, or information necessary to support the results or interpretations presented in the discussion. |
Supplemental data | Essential datasets that are too large or cumbersome to include in the paper. Especially for papers that include “big data” (like sequencing or modeling results), this is often where the real, raw data is presented. |
Research articles typically contain each of these sections, although sometimes the “results” and “discussion” sections (or “discussion” and “conclusion” sections) are merged into one section. Additional sections may be included, based on request of the journal or the author(s). Keep in mind: If it was included, someone thought it was important for you to read.
Published papers are not truths etched in stone. Published papers in high impact journals are not truths etched in stone. Published papers by bigwigs in the field are not truths etched in stone. Published papers that seem to agree with your own hypothesis or data are not etched in stone. Published papers that seem to refute your hypothesis or data are not etched in stone.
Science is a never-ending work in progress, and it is essential that the reader pushes back against the author’s interpretation to test the strength of their conclusions. Everyone has their own perspective and may interpret the same data in different ways. Mistakes are sometimes published, but more often these apparent errors are due to other factors such as limitations of a methodology and other limits to generalizability (selection bias, unaddressed, or unappreciated confounders). When reading a paper, it is important to consider if these factors are pertinent.
Critical thinking is a tough skill to learn but ultimately boils down to evaluating data while minimizing biases. Ask yourself: Are there other, equally likely, explanations for what is observed? In addition to paying close attention to potential biases of the study or author(s), a reader should also be alert to one’s own preceding perspective (and biases). Take time to ask oneself: Do I find this paper compelling because it affirms something I already think (or wish) is true? Or am I discounting their findings because it differs from what I expect or from my own work?
The phenomenon of a self-fulfilling prophecy, or expectancy, is well studied in the psychology literature [ 2 ] and is why many studies are conducted in a “blinded” manner [ 3 ]. It refers to the idea that a person may assume something to be true and their resultant behavior aligns to make it true. In other words, as humans and scientists, we often find exactly what we are looking for. A scientist may only test their hypotheses and fail to evaluate alternative hypotheses; perhaps, a scientist may not be aware of alternative, less biased ways to test her or his hypothesis that are typically used in different fields. Individuals with different life, academic, and work experiences may think of several alternative hypotheses, all equally supported by the data.
The author(s) are human too. So, whenever possible, give them the benefit of the doubt. An author may write a phrase differently than you would, forcing you to reread the sentence to understand it. Someone in your field may neglect to cite your paper because of a reference count limit. A figure panel may be misreferenced as Supplemental Fig 3E when it is obviously Supplemental Fig 4E. While these things may be frustrating, none are an indication that the quality of work is poor. Try to avoid letting these minor things influence your evaluation and interpretation of the work.
Similarly, if you intend to share your critique with others, be extra kind. An author (especially the lead author) may invest years of their time into a single paper. Hearing a kindly phrased critique can be difficult but constructive. Hearing a rude, brusque, or mean-spirited critique can be heartbreaking, especially for young scientists or those seeking to establish their place within a field and who may worry that they do not belong.
To truly understand a scientific work, you often will need to look up a term, dig into the supplemental materials, or read one or more of the cited references. This process takes time. Some advisors recommend reading an article three times: The first time, simply read without the pressure of understanding or critiquing the work. For the second time, aim to understand the paper. For the third read through, take notes.
Some people engage with a paper by printing it out and writing all over it. The reader might write question marks in the margins to mark parts (s)he wants to return to, circle unfamiliar terms (and then actually look them up!), highlight or underline important statements, and draw arrows linking figures and the corresponding interpretation in the discussion. Not everyone needs a paper copy to engage in the reading process but, whatever your version of “printing it out” is, do it.
Talking about an article in a journal club or more informal environment forces active reading and participation with the material. Studies show that teaching is one of the best ways to learn and that teachers learn the material even better as the teaching task becomes more complex [ 4 – 5 ]; anecdotally, such observations inspired the phrase “to teach is to learn twice.”
Beyond formal settings such as journal clubs, lab meetings, and academic classes, discuss papers with your peers, mentors, and colleagues in person or electronically. Twitter and other social media platforms have become excellent resources for discussing papers with other scientists, the public or your nonscientist friends, or even the paper’s author(s). Describing a paper can be done at multiple levels and your description can contain all of the scientific details, only the big picture summary, or perhaps the implications for the average person in your community. All of these descriptions will solidify your understanding, while highlighting gaps in your knowledge and informing those around you.
One approach we like to use for communicating how we build on the scientific literature is by starting research presentations with an image depicting a wall of Lego bricks. Each brick is labeled with the reference for a paper, and the wall highlights the body of literature on which the work is built. We describe the work and conclusions of each paper represented by a labeled brick and discuss each brick and the wall as a whole. The top brick on the wall is left blank: We aspire to build on this work and label this brick with our own work. We then delve into our own research, discoveries, and the conclusions it inspires. We finish our presentations with the image of the Legos and summarize our presentation on that empty brick.
Whether you are reading an article to understand a new topic area or to move a research project forward, effective learning requires that you integrate knowledge from multiple sources (“click” those Lego bricks together) and build upwards. Leveraging published work will enable you to build a stronger and taller structure. The first row of bricks is more stable once a second row is assembled on top of it and so on and so forth. Moreover, the Lego construction will become taller and larger if you build upon the work of others, rather than using only your own bricks.
Build on the article you read by thinking about how it connects to ideas described in other papers and within own work, implementing a technique in your own research, or attempting to challenge or support the hypothesis of the author(s) with a more extensive literature review. Integrate the techniques and scientific conclusions learned from an article into your own research or perspective in the classroom or research lab. You may find that this process strengthens your understanding, leads you toward new and unexpected interests or research questions, or returns you back to the original article with new questions and critiques of the work. All of these experiences are part of the “active reading”: process and are signs of a successful reading experience.
In summary, practice these rules to learn how to read a scientific article, keeping in mind that this process will get easier (and faster) with experience. We are firm believers that an hour in the library will save a week at the bench; this diligent practice will ultimately make you both a more knowledgeable and productive scientist. As you develop the skills to read an article, try to also foster good reading and learning habits for yourself (recommendations here: [ 6 ] and [ 7 ], respectively) and in others. Good luck and happy reading!
Thank you to the mentors, teachers, and students who have shaped our thoughts on reading, learning, and what science is all about.
MAC was supported by the PhRMA Foundation's Postdoctoral Fellowship in Translational Medicine and Therapeutics and the University of Virginia's Engineering-in-Medicine seed grant, and KLS was supported by the NIH T32 Global Biothreats Training Program at the University of Virginia (AI055432). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
When starting a new research project, it is important to develop a sound research question. This is a crucial step in the research process, as it will guide your research activity. Therefore, you should not rush to write an effective research question.
A properly written research question has several characteristics.
Often, you already have a broader subject that interests you. For example, say organismal biology. However, this alone will get you nowhere, whether you are a graduate student or professor writing for a grant. Following steps can help you to organize priorities.
Aspects of feasibility are best tested in pilot studies or modeling scenarios. Here, you could factor in costs in terms of time, labor, and tools.
Review your questions carefully. Take these three for instance.
A) How is global biodiversity maintained?
B) Which biotic processes contribute most to maintaining local plant diversity in Western Amazonian forests?
C) What limited biodiversity at site X in Amazonia in the last 5 years?
(A) is much too broad – there are many possible processes, and these will vary geographically. However, (C) is too narrow and probably impossible to answer. (B) is neither too narrow nor too broad. It is specific enough to guide a research project and is feasible.
Likewise, a too objective question will limit you. Take “How many species of trees are there in New England forests”. This is factual information now. So it does not lend itself to argumentation. A more subjective question would be “What is the relationship between climate change and tree diversity dynamics in New England forests?” Also, try to avoid overly simplistic questions (e.g. “Where do forest fires occur most?”), which could be answered with Web searches nowadays. Instead, ask something more complex, like “What are the effects of logging on forest fire frequency and intensity?”
Be flexible and adaptable. A good research question is not permanent. Do not be afraid to modify your research question, revising it as you investigate it more. For example, key data may be lacking, or a new study is published that challenges some presumptions you had. In hypothesis-driven research, a good research question can easily be transformed into a testable hypothesis.
In sum, an effective research question is thoughtfully formulated. It interests not only you but potentially other researchers as well. It should follow accepted ethical standards (honesty, no stealing of ideas or fabrication of data, or no harming of human/animals subjects). A useful rule-of-thumb for a well-formulated research question is to follow Hulley et al .’s “FINER”: feasible, interesting, novel, ethical, and relevant.
In what part of your research do you find your research question?
Hi Stephen, Thank you for your question. Your research question should ideally be identified before you start your work. Research questions are based on research gaps and the latter becomes evident while conducting a comprehensive literature survey, prior to initiating any kind of research activity. Your entire work plan would be based on the question that you are trying to address through your research. Did you get a chance to install our FREE Mobile App . Make sure you subscribe to our weekly newsletter .
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In some cases, such as for a course assignment or a research project you're working on with a faculty member, your research question will be determined by your professor. If that's the case, you can move on to the next step . Otherwise, you may need to explore questions on your own.
A few suggestions:
Watch the videos in this section for advice on developing your research question and considerations related to choosing a topic for which you have a strong opinion.
Silke Haidekker has a PhD in Pharmacology from the University of Hannover. She is a Clinical Research Associate in multiple pharmaceutical companies in Germany and the USA. She now works as a full-time medical translator and writer in a small town in Georgia.
You would probably agree that the time spent writing your PhD dissertation or thesis is not only a time of taking pride or even joy in what you do, but also a time riddled with panic attacks of different varieties and lengths. When I worked on my PhD thesis in pharmacology in Germany many years back, I had my first panic attack as I first learned how to kill rats for my experiments with a very ugly tool called a guillotine! After that part of the procedure, I was to remove and mash their livers, spike them with Ciclosporin A (an immunosuppressive agent), and then present the metabolites by high-pressure liquid chromatography.
Many rats later, I had another serious panic attack. It occurred at the moment my doctoral adviser told me to write my first research paper on the Ciclosporin A metabolites I had detected in hundreds of slimy mashes of rat liver. Sadly, this second panic attack led to a third one that was caused by living in the pre-internet era, when it was not as easy to access information about how to write research papers .
How I got over writing my first research paper is now ancient history. But it was only years later, living in the USA and finally being immersed in the language of most scientific research papers, that my interest in the art of writing “good” research papers was sparked during conferences held by the American Medical Writers Association , as well as by getting involved in different writing programs and academic self-study courses.
Good writing begins with clearly stating your research question (or hypothesis) in the Introduction section —the focal point on which your entire paper builds and unfolds in the subsequent Methods, Results, and Discussion sections . This research question or hypothesis that goes into the first section of your research manuscript, the Introduction, explains at least three major elements:
B) what is still unknown (or problematic), c) what is the question or hypothesis of your investigation.
Some medical writers refer to this organizational structure of the Introduction as a “funnel shape” because it starts broadly, with the bigger picture, and then follows one scientifically logical step after the other until finally narrowing down the story to the focal point of your research at the end of the funnel.
Let’s now look in greater detail at a research question example and how you can logically embed it into the Introduction to make it a powerful focal point and ignite the reader’s interest about the importance of your research:
You should start by giving your reader a brief overview of knowledge or previous studies already performed in the context of your research topic.
The topic of one of my research papers was “investigating the value of diabetes as an independent predictor of death in people with end-stage renal disease (ESRD).” So in the Introduction, I first presented the basic knowledge that diabetes is the leading cause of end-stage renal disease (ESRD) and thus made the reader better understand our interest in this specific study population. I then presented previous studies already showing that diabetes indeed seems to represent an independent risk factor for death in the general population. However, very few studies had been performed in the ESRD population and those only yielded controversial results.
Example : “It seems well established that there is a link between diabetic nephropathy and hypertensive nephropathy and end-stage renal disease (ESRD) in Western countries. In 2014, 73% of patients in US hospitals had comorbid ESRD and type 2 diabetes (1, 2, 3)…”
In our example, this “controversy” flags the “unknown” or “problematic” and therefore provides strong reasons for why further research is justified. The unknown should be clearly stated or implied by using phrases such as “were controversial” (as in our example), “…has not been determined,” or “…is unclear.” By clearly stating what is “unknown,” you indicate that your research is new. This creates a smooth transition into your research question.
Example : “However, previous studies have failed to isolate diabetes as an independent factor, and thus much remains unknown about specific risk factors associated with both diabetes and ESRD .”
Your research question is the question that inevitably evolves from the deficits or problems revealed in the “Unknown” and clearly states the goal of your research. It is important to describe your research question in just one or two short sentences, but very precisely and including all variables studied, if applicable. A transition should be used to mark the transition from the unknown to the research question using one word such as “therefore” or “accordingly,” or short phrases like “for this reason” or “considering this lack of crucial information.”
In our example, we stated the research question as follows:
Example : “Therefore, the primary goal of our study was to perform a Kaplan-Meier survival study and to investigate, by means of the Cox proportional hazard model, the value of diabetes as an independent predictor of death in diabetic patients with ESRD.”
Note that the research question may include the experimental approach of the study used to answer the research question.
Another powerful way to introduce the research question is to state the research question as a hypothesis so that the reader can more easily anticipate the answer. In our case, the question could be put as follows:
Example : “To test the hypothesis that diabetes is an independent predictor of death in people with ESRD, we performed a Kaplan-Survival study and investigated the value of diabetes by means of the Cox proportional hazard model.”
Note that this sentence leads with an introductory clause that indicates the hypothesis itself, transitioning well into a synopsis of the approach in the second half of the sentence.
The generic framework of the Introduction can be modified to include, for example, two research questions instead of just one. In such a case, both questions must follow inevitably from the previous statements, meaning that the background information leading to the second question cannot be omitted. Otherwise, the Introduction will get confusing, with the reader not knowing where that question comes from.
To conclude, here is my simple but most important advice for you as a researcher preparing to write a scientific paper (or just the Introduction of a research paper) for the first time: Think your research question through precisely before trying to write it down; have in mind the reasons for exactly why you wanted to do this specific research, what exactly you wanted to find out, and how (by which methods) you did your investigation. If you have the answers to these questions in mind (or even better, create a comprehensive outline ) before starting the paper, the actual writing process will be a piece of cake and you will finish it “like a rat up a drainpipe”! And hopefully with no panic attacks.
Before submitting your master’s thesis or PhD dissertation to academic journals for publication, be sure to receive proofreading services (including research paper editing , manuscript editing , thesis editing , and dissertation editing ) to ensure that your research writing is error-free. Impress your journal editor and get into the academic journal of your choice.
Answered by: david hisle last updated: aug 30, 2022 views: 66353.
These guidelines can help you identify a research study and distinguish an article that presents the findings of a research study from other types of articles.
Research studies are almost always published in peer-reviewed (scholarly) journals. The articles often contain headings similar to these: Literature Review, Method, Results, Discussion , and Conclusion .
Articles that review other studies without presenting new research results are not research studies. Examples of article types that are NOT research studies include:
Some databases allow you to limit by publication type. Use this feature to help identify research studies. Here are tips for limiting by publication type in several popular databases:
ERIC via EBSCO host :
Some databases, like Sociological Abstracts , and Social Work Abstracts allow you to limit to "Articles" or "Abstracts of Journal Articles," but do not have more specific publication types. In Sociological Abstracts , a quick and dirty way to find research studies is to limit to "Articles" and then add "tables" to your search. This works because most research studies contain tables, and this is an indexed field in this database. For example, you might search for "gender and tables." This doesn't work well in Social Work Abstracts , though, because "tables" is not indexed. Instead, try something like "gender and research study" or even "gender and study." In all of these examples, you need to carefully examine the abstracts to see if the articles meet the requirements of a research study.
Many of the EBSCO host databases (e.g., Academic Search Complete , Health Source Nursing/Academic Edition, Sociological Collection ) allow you to limit to peer reviewed journals, but not by specific publication type. Be sure to click in the box to limit to peer reviewed journals. Then, add terms like "research study," "empirical," or "longitudinal" to your search. Again, carefully examine the abstracts to see if the articles meet the requirements of a research study.
Here is an example of an abstract of a research study from Sociological Collection . Phrases that help identify it as a research study are in bold:
Self-pity is a frequent response to stressful events. So far, however, empirical research has paid only scant attention to this subject. The present article aims at exploring personality characteristics associated with individual differences in feeling sorry for oneself . Two studies with N=5141 and N=5161 university students were conducted, employing multidimensional measures of personality, control beliefs, anger, loneliness, and adult attachment. With respect to personality, results showed strong associations of self-pity with neuroticism, particularly with the depression facet. With respect to control beliefs, individuals high in self-pity showed generalized externality beliefs, seeing themselves as controlled by both chance and powerful others. With respect to anger expression, self-pity was primarily related to anger-in. Strong connections with anger rumination were also found. Furthermore, individuals high in self-pity reported emotional loneliness and ambivalent-worrisome attachments. Finally, in both studies, a strong correlation with gender was found, with women reporting more self-pity reactions to stress than men. Findings are discussed with respect to how they support, extend, and qualify the previous literature on self-pity, and directions for future empirical research are pointed out.
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When reviewing research that you have found, start by reading the abstract in order to identify the methodologies used in the study. Research articles should also include a section that describes the methods used in more detail.
Not all quantitative or qualitative studies will include the same clues present in the examples on this page. Read articles carefully to understand the methodologies used.
This abstract has several indications that this is a quantitative study:
This abstract has several indications that this is a qualitative study:
Created by Joshua Vossler
Make a list of keywords relevant to your topic. Be sure to list similar, broader, narrower, and related terms . Keep the list by your side when you start your research and continue to add to it as you come across useful terms.
Before searching for information, you need to identify keywords related to your topic. The keywords you use have an impact on the results of your research.
If the keywords you choose do not give you the results you need, try the others on your list or use the search strategies listed under Step 2.
Keywords and phrases can easily be found by scanning . . .
If you are still struggling, try these suggestions:
When researching, we are like detectives trying to combine the right terms in the right place to find the information we need. This information will help you combine search terms to find relevant sources.
Broad Search
Search for information using the single most important term related to your topic. Use this type of search when looking for basic background information.
Specific Search
Search for information by combining key concepts using the words you have brainstormed. Each concept/word should be separated by the word "AND" . Use this kind of search when looking for specific evidence related to your claim or thesis.
Getting Too Many Irrelevant Results?
Add more search terms.
Getting Too Few Relevant Results?
Change or remove some search terms.
A concept map is a graphical tool used to organize and structure knowledge.
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Home » Research Gap – Types, Examples and How to Identify
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Definition:
Research gap refers to an area or topic within a field of study that has not yet been extensively researched or is yet to be explored. It is a question, problem or issue that has not been addressed or resolved by previous research.
Identifying a research gap is an essential step in conducting research that adds value and contributes to the existing body of knowledge. Research gap requires critical thinking, creativity, and a thorough understanding of the existing literature . It is an iterative process that may require revisiting and refining your research questions and ideas multiple times.
Here are some steps that can help you identify a research gap:
There are different types of research gaps that can be identified, and each type is associated with a specific situation or problem. Here are the main types of research gaps and their explanations:
This type of research gap refers to a lack of theoretical understanding or knowledge in a particular area. It can occur when there is a discrepancy between existing theories and empirical evidence or when there is no theory that can explain a particular phenomenon. Identifying theoretical gaps can lead to the development of new theories or the refinement of existing ones.
An empirical gap occurs when there is a lack of empirical evidence or data in a particular area. It can happen when there is a lack of research on a specific topic or when existing research is inadequate or inconclusive. Identifying empirical gaps can lead to the development of new research studies to collect data or the refinement of existing research methods to improve the quality of data collected.
This type of research gap refers to a lack of appropriate research methods or techniques to answer a research question. It can occur when existing methods are inadequate, outdated, or inappropriate for the research question. Identifying methodological gaps can lead to the development of new research methods or the modification of existing ones to better address the research question.
A practical gap occurs when there is a lack of practical applications or implementation of research findings. It can occur when research findings are not implemented due to financial, political, or social constraints. Identifying practical gaps can lead to the development of strategies for the effective implementation of research findings in practice.
This type of research gap occurs when there is a lack of knowledge or information on a particular topic. It can happen when a new area of research is emerging, or when research is conducted in a different context or population. Identifying knowledge gaps can lead to the development of new research studies or the extension of existing research to fill the gap.
Here are some examples of research gaps that researchers might identify:
Examples of Research Gap In Literature Review, Thesis, and Research Paper might be:
By following these steps, you can effectively write about research gaps in your paper and clearly articulate the contribution that your study will make to the existing body of knowledge.
Here are some steps to follow when writing about research gaps in your paper:
The importance of research gaps can be summarized as follows:
Here are some potential applications of research gap:
Here are some of the advantages of research gap:
While research gaps can be advantageous, there are also some potential disadvantages that should be considered:
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Last updated : July 18, 2024
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Most professors will require the use of academic (AKA peer-reviewed) sources for student writing. This is because these sources, written for academic audiences of specific fields, are helpful for developing your argument on many topics of interest in the academic realm, from history to biology. While popular sources like news articles also often discuss topics of interest within academic fields, peer-reviewed sources offer a depth of research and expertise that you cannot find in popular sources. Therefore, knowing how to (1) identify popular vs. academic sources, (2) differentiate between primary and secondary sources, and (3) find academic sources is a vital step in writing research. Below are definitions of the two ways scholars categorize types of sources based on when they were created (i.e. time and place) and how (i.e. methodology):
Finding appropriate academic sources from the hundreds of different journal publications can be daunting. Therefore, it is important to find databases –digital collections of articles–relevant to your topic to narrow your search. Albertson’s Library has access to several different databases, which can be located by clicking the “Articles and Databases” tab on the website’s homepage, and navigating to “Databases A-Z” to refine your search. Popular databases include: Academic Search Premier and Proquest Central (non-specific databases which include a wide variety of articles), JSTOR (humanities and social sciences, from literature to history), Web of Science (formal sciences and natural sciences such as biology and chemistry), and Google Scholar (a web search engine that searches scholarly literature and academic sources). If you are unable to access articles from other databases, make sure you’re signed in to Alberton’s Library through Boise State!
Databases include many different types of sources besides academic journals, however, including book reviews and other periodicals. Using the search bar , you can limit search results to those containing specific keywords or phrases like “writing center” or “transfer theory.” Utilizing keywords in your search–names of key concepts, authors, or ideas–rather than questions is the most effective way to find articles in databases. When searching for a specific work by title, placing the title in quotation marks will ensure your search includes only results in that specific word order. In the example below, search terms including the author (“Virginia Woolf”) and subject (“feminism”) are entered into the popular database EBSCOhost:
Many databases have a bar on the left of the screen where you can further refine your results. For example, if you are only interested in finding complete scholarly articles, or peer-reviewed ones, you can toggle these different options to further limit your search. These options are located under the “Refine Results” bar in EBSCOhost, divided into different sections, with a display of currently selected search filters and filter options to refine your search based on your specific needs, as seen in the figure below:
Search results can also be limited by subject : If you search “Romeo and Juliet” on Academic Search Premier to find literary analysis articles for your English class, you’ll find a lot of other sources that include this search term, such as ones about theater production or ballets based on Shakespeare’s play. However, if you’re writing a literary paper on the text of the play itself, you might limit your search results to “fiction” to see only articles that discuss the play within the field of literature. Alternatively, for a theater class discussing the play, you might limit your search results to “drama.”
BMC Health Services Research volume 24 , Article number: 824 ( 2024 ) Cite this article
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Practice-based research is one of the levers identified by the World Health Organization (WHO) to strengthen primary health care. The scaling of health and social care innovations has the potential to reduce inequities in health and to expand the benefits of effective innovations. It is now rapidly gaining the attention of decision-makers in health and social care, particularly in high-income countries.
To meet the challenge of declining numbers of primary care physicians in France, Multi-professional Healthcare Centers (MHC) were created to bring together medical and paramedical professionals. They are a source of innovation in meeting the health challenges facing our populations.
Specific methodology exists to identify health innovations and assess their scalability. A working group, including end-users and specialists, has adapted this methodology to the French context and the University department of general practice of Montpellier-Nîmes (France) launched a pilot study in Occitanie, a French region.
To identify and evaluate the scalability of innovations produced in pluri-professional healthcare centers in the Occitanie region.
A pilot, observational, cross-sectional study was carried out. The SPRINT Occitanie study was based on a questionnaire with two sections: MHC information and the modified Innovation Scalability Self-Administered Questionnaire (ISSaQ), version 2020. The study population was all 279 MHC in the Occitanie region.
19.3% (54) of MHC in the Occitanie region, responded fully or incompletely to the questionnaire. Four out of 5 U-MHCs were represented. Five MHC presented multiple innovations. The average per MHC was 1.94 (± 2.4) innovations. 26% of them ( n = 9) had high scalability, 34% ( n = 12) medium scalability and 40% ( n = 14) low scalability. The main innovation represented (86%) were healthcare program, service, and tool.
In our cross-sectional study, a quarter of the innovations were highly scalable. We were able to demonstrate the importance of MHC teams in working on primary care research through the prism of innovations. Primary-care innovations must be detected, evaluated, and extracted to improve their impact on their healthcare system.
Peer Review reports
Primary health care-oriented health systems are organized with the goal to provide the highest attainable level of outpatient healthcare services, while maximizing equity and solidarity [ 1 ]. Primary health care-oriented research is one of the 10 operational levers identified by the World Health Organization (WHO) to strengthen them [ 2 ]. The scaling of health and social care innovations has the potential to reduce inequities in health and to expand the benefits of effective innovations [ 3 , 4 , 5 ]. WHO defines health innovations as a new or improved solution with the transformative ability to accelerate positive health impact [ 6 ]. They are now rapidly gaining the attention of decision-makers, particularly in high-income countries [ 7 ]. They are faced with complex health and social care systems, aging populations and limited financial and human resources, justifying the need to prioritize effective scaling of beneficial innovations [ 8 , 9 , 10 , 11 ].
The number of French primary care doctors has fallen by 8% between 2012 and 2022 [ 12 ]. Nearly 11% of French people over the age of 17 did not have a general practitioner in 2022, and 30% lived in a "medical desert" [ 13 , 14 ]. The crisis in access to healthcare is a major concern for the French population and other high-income countries [ 15 ]. The healthcare system must be updated to include organizational innovations [ 16 ]. To meet these challenges, the French government enabled the creation of multi-professional health care centers (MHCs) from 2007. An MHC is made up of at least 2 general practitioners and at least one health auxiliary such as a pharmacist, midwife, nurse, physiotherapist, speech therapist or other regulated health profession. In 2023, 2251 MHCs were in activity throughout France [ 17 ] and the goal is to double their number by 2026 [ 18 ].
The dynamics of coordinated care in France are recent. In Quebec, it began in the 1970s with the creation of local community service centers (CLCS) where patients could consult several health professionals, in conjunction with the national social security system [ 19 ].
Canada has launched promising pilot projects that, however, were not scaled [ 17 ]. To mitigate this issue, Quebec's Sustainable Health Research Center has developed a research program aiming at identifying innovations produced by primary care facilities, classify them and evaluate their scalability [ 11 ].
We launched a pilot study to replicate their study in Occitanie, a French region, named SPRINT Occitanie ( Soins PRimaires INnovations et Territoires en Occitanie ). The original study found 25% of innovations were highly scalable (ref 11 again). Considering Quebec’s extensive experience on innovation scale-up, our research hypothesis was that PHCs produce innovations in Occitanie, but in fewer numbers and less scalable in comparison.
Nearly 83% of the region's territory is under-dense in terms of access to general practice [ 20 ]. It counted 279 MHCs in March 2023, including 5 with the “University” label [ 21 ]. This label identifies U-MHCs whose role is to coordinate between care facilities, the regional agency and the medical faculty of the nearest university, to bring together research, innovation and teaching [ 22 ]. Occitanie has three university hospital centers: Toulouse, Montpellier and Nîmes. They have organized a complete ecosystem to support innovation based on Clinical Research and Innovation Delegations, which are integrated into the university hospitals. Montpellier and Nîmes also share an innovation extractor [ 23 ]. Such ecosystems are not accessible to primary care, yet. Designing innovation extractors for primary care, in conjunction with pre-existing innovation ecosystems, could enable to better structure innovations that are more scalable and efficient, and better adapted to local needs. There is, to date, no incentive policy for evaluating and scaling up innovations for MHC. Only U-MHC are invited to do so, without allocating resources for this purpose. No study has identified healthcare innovations in MHCs in the Occitanie region, nor assessed their scalability.
The objective of this pilot study was to identify and assess the scalability of innovations produced in MHCs in the Occitanie region.
A pilot, observational, cross-sectional study was carried out between January and March 2023.
Innovations were defined as what was perceived as new by MHC staff [ 24 , 25 ]. To ensure harmonization, we gave respondents the WHO definition of innovation. Each person was then able to interpret the innovative or non-innovative nature of the initiatives in their MHC.
The SPRINT Occitanie study was based on a questionnaire with two sections (MHC information and the modified ISSaQ questionnaire).
It was reported as per guidelines for internet e-surveys [ 26 ] and in line with the CHERRIES checklist [ 27 ].
The first 16 questions (Additional file 1) were designed to identify the MHCs and respective innovations. These included: name of the MHC, single or multi-site nature, commune, status of the person answering the questionnaire (manager, coordinator, doctor, or other), e-mail address. It also included detailed information on the MHCs: year of creation, number of professionals, number of general practitioners, number of doctors in other specialties, number of university internship supervisors, previous responses to calls for projects (care, teaching or research), collaboration with the inter-regional grouping for clinical research and innovation (GIRCI). Specific information on innovations included were the name and abbreviation, description of the innovation, links with potential partners, communication around the project and purpose of the innovation. To characterize the type of innovation, the MHC correspondent had several modalities: program, model, approach, tool, instrument, indicator, algorithm, service, policy, practice or other, taken from the WHO's International Classification of Health Interventions [ 28 ]. This classification comprises three main axes: the target (entity on which the action was carried out), the action (act carried out by an actor on the target), and the means (processes and methods by which the action was carried out). Finally, the MHC correspondent could opt to have feedback on the scalability assessment.
The second section was adapted from the Innovation Scalability Self-Administered Questionnaire (ISSaQ), version of 2020 [ 11 ]. This questionnaire was adapted to suit the idioms of metropolitan French. The SPRINT Occitanie project team consisted of the questionnaire's end-users (teacher-researchers in general practice and MHC coordinators), a hospital specialist in innovation extraction and a public health physician methodologist. The questionnaire was tested with five MHC coordinators to check comprehension and confirm completion time. Concrete examples clarifying the questions were added following their feedback. The original questionnaire (ISSaQ) and the adapted questionnaire (modified ISSaQ) are presented in Additional file 2.
The ISSaQ assessed data availability for three dimensions (theory, impact and coverage) with 16 closed questions and 6 possible answers: “Yes, No, Not planned, Not applicable or Under evaluation”. If “yes”, the user could complete the answer by mentioning what data or elements were related to the question in free text. The Theory dimension included a question on the conceptual model that may or may not have informed the development of the innovation. The Impact dimension assessed data on six elements: acceptability, feasibility, appropriation, potential effectiveness in an experimental context, effectiveness in a real-life context, and documentation of results. For the last dimension, Coverage , we could have answers on the scope of the innovation, its adoption by the MHC team, fidelity in implementation, sustainability, implementation in another context, compatibility with other similar interventions, conformity with health policy guidelines in the context, and finally, the presence of data on cost-effectiveness and financial and human resource requirements.
This questionnaire was transposed onto LimeSurvey software, licensed by the University of Montpellier, to be self-administered by each MHC correspondent in Occitanie.
It was possible to complete the questionnaire for a single innovation. If the MHC wished to identify more than one, the correspondent could restart the questionnaire at the beginning.
The study population was all 279 MHCs in the Occitanie region that had received the regional health agency label. Health centers and communities of healthcare professionals were not included. In each MHC, a correspondent completed the open survey. This could be the coordinator, the manager, a medical doctor or another active member of the structure. To contact them, several e-mail reminders were sent by the university department of general practice of Montpellier-Nîmes and Toulouse to the university internship supervisor attached to them. Also, the Federation of Pluriprofessional Coordinated Practice [Fédération de l’Exercice Coordonné Pluriprofessionnel] (FECOP) contacted its members on 3 occasions, and the regional health agency of Occitanie, contacted all the MHC in the region. The FECOP is commissioned by regional health agency to support MHCs in project in the region, associated care teams in a network, offer them training and pool their innovations [ 29 ].
After collecting the data, three members of our research team proposed a blind classification of the respondent's category. After seeing the four proposals, a consensus was made by two of the three members based on the WHO definitions. The scalability score was calculated, as stipulated by ISSaQ, by summing up only positive responses to the 16 scalability criteria. Responses of "No, not applicable, under evaluation or not planned" were considered null. The score obtained, a maximum of 16, was then classified into 3 categories in accordance with the proposals of Ben Charif et al . [ 30 ]. This hierarchical classification was made according to 3 modalities: "high" (scalability greater than or equal to 10), "low" (scalability less than or equal to 3) and “medium" for the remainder.
Descriptive statistics described demographic characteristics using frequencies with percentages for categorical variables and means and standard deviations or medians and interquartile ranges for continuous variables. Only complete responses (meeting all 16 scalability criteria) were analysed.
Statistical analyses were carried out partly using Microsoft Excel® version 2304 and RStudio® version 2023.03.1 using version R 4.2.3 with the package "stats" version 4.2.3.
Between January and March 2023, 35 complete responses, i.e., 35 innovations, were collected from 18 different MHCs (Fig. 1 ).
SPRINT Occitanie study flow chart
The Checklist for Reporting Results of Internet E-Surveys (CHERRIES) is in Additional file 3.
19.3% of MHCs in the Occitanie region, i.e. 54 MHCs, responded fully or incompletely to the questionnaire. Among these, 35 questionnaires from 18 MHC were complete and analysed. Five MHCs presented multiple innovations: 11 for the U-MHC in Cabestany (Pyrénées-Orientales), 5 for the U-MHC in Vergèze (Gard), and 2 for the MHC in Mende (Lozère), the MHC in Bessèges (Gard) and the MHC in Pont-St-Esprit (Gard) (Table 1 ). The average per MHC was 1.94 (± 2.4) innovations. The MHC that responded incompletely were contacted to offer support in completing the questionnaire, yet none responded.
The MHCs were recent, mainly multi-site (89%) and mostly located in Eastern Occitanie (83%) (Table 1 ).
Most innovations (86%) concerned a healthcare program ( n = 11, 31%), a patient service ( n = 10, 29%) or a tool ( n = 9, 26%) (Fig. 2 ). We assessed the scalability levels of the described innovations (Figs. 2 and 3 ).
Scalability ranking by category of innovations
Categories of innovations by scalability ranking
26% of innovations ( n = 9) had high scalability, 34% ( n = 12) medium scalability and 40% ( n = 14) low scalability. Additional file 4 lists the name of the innovation and the MHC that described it, by scalability level group.
Over half of the evaluated innovations (60%) had a high or medium scalability score. Particularly, nine interventions were highly scalable, and mostly pertained to the program category ( n = 5, 26%) (Fig. 2 ).
The results of the number of modified ISSaQ criterion to assess innovation scalability showed the average score for all innovations was 5.86 (± 3.98) (Table 2 ).
On average, 51% of innovations had an assessment for the "theory" dimension, 35% for the "impact" dimension, 38% for the "coverage" dimension and 28% for the "cost" dimension (Table 2 ). Additional file 4 contains a list of all innovations, with all criteria, evaluated or not. The empirical maximum scalability score was 13, and the minimum was 0.
This study aimed at identifying innovations produced in MHCs in the Occitanie region, and evaluating their scalability. To this end, we replicated a previous study that reported 25% of highly scalable innovations among 24 analysed innovations, and we hypothesized lower rates of highly scalable innovations given the more recent nature of our region’s primary care coordinated networks. Our study analyzed 18 PHCs in the Occitanie region, which presented 35 innovations. We identified multiple innovations per MHC, but few MHCs are represented in the results (18 out of 279). We found the average scalability of around 6, arguably low compared with previous studies that reported an average scalability of 11 [ 11 ]. This result was expected, confirming our initial hypothesis, and several factors may explain it. The dynamics of coordinated care in France are recent, particularly when compared with Quebec.It is still difficult for MHC teams to get involved in research projects, as they are not very well structured. Encouragingly, 44% of the MHCs in the study have already received funding through calls for projects.
Between 2012 and 2017, the Ministry of Health and Prevention's objective was to label one U-MHC per department, with the aim of carrying out networked primary care research [ 22 , 31 ]. We note that 4 of the 5 U-MHCs in Occitanie took part in our study, resulting in a high representation. The structuring of a network of U-MHCs is currently underway as part of the F-CRIN project, led by the supervisory ministries in conjunction with the French National Council of Teaching Generalists [ 32 ]. The GIRCIs are responsible for the coordination of regional initiatives and providing support to healthcare establishments, facilities and centers in the field of applied health research and innovation [ 33 ]. They run calls for projects, such as RESPIR (Inter-Regional Primary Care Research) since 2021. Only three MHCs indicated that they had worked with the GIRCI. It should be noted that these were the two oldest U-MHCs in the region, and the MHC where the FECOP manager works. These factors should not obscure the fact that research is at an early stage of maturity for all MHC care teams. Our results reflected this since, despite of predominantly high and medium scalability scores, there was still a substantial number of low scalability innovations, and difficulties in responding to the questionnaire criteria reported by participating teams. There is a risk of a breach of equality between the pilot structures and the others. This shows how important it is to structure a local network, clearly identified by the MHCs' correspondents, to help them design and improve their innovations. Still, these laid foundations will allow the creation of an ecosystem that benefits and reaches all. Altogether, these collective initiatives involving public institutions and university laboratories should provide medium- and long-term opportunities for the creation of health innovations and respective scaling [ 34 ].
The main limitation of this study stems from the study design, as cross-sectional studies imply selection bias. Some MHCs responded several times, leading to a potential desirability bias. We tried to mitigate this by taking care to contact each MHC several times, using several different email addresses senders as well as other communication channels. This was an exploratory study, not intended to be exhaustive. We kept the questionnaire open online for 3 months, to give as many MHC correspondents as possible time to respond. Ranking biases, notably memorization bias, linked to self-administration of the questionnaire, were mitigated by making each scalability criterion explicit via a concrete example that was threaded throughout the questionnaire. We also provided a contact person to help correspondents. In some MHCs, several correspondents answered the questionnaire together, but we did not quantify this, nor do we know the rate at which the questionnaire was reviewed. The ISSaQ was updated in March 2023, implying further refinement. It incorporates Likert scales and new criteria for assessing scalability have been added [ 35 ]. In our scalability analysis, each criterion has the same weight as the others, although some are more relevant to one type of innovation than others.
SPRINT Occitanie was based on a Canadian study in a different and not very comparable healthcare system.
Our success in mobilizing one-fifth of the MHCs in Occitanie is encouraging, but it also shows that most of them are still far removed from the research dimension. Most responses came from MHC with University training supervisors, in conjunction with the Montpellier-Nîmes Faculty of Medicine, which carried out the study.
The exploratory work carried out by the SPRINT Occitanie study is a first step. The creation of a website, considering appropriate scalability questionnaire, could enable us to collect future innovations and build an extractor for primary care in the long term. This site could be the entry and development base for innovations in primary care. The innovation ecosystem of university hospitals and universities should be key partners. This could help creating a virtuous cycle raising questions from practice, conducting experiments, finding results, and producing evidence that can serve the purpose of improving patient care and the health of the population [ 36 ].
Practice-based research supporting the development, implementation, and evaluation of innovations in primary care contributes to the improvement of patient care and the health of the population [ 36 ]. Our study showed there are promising foundations, with numerous and diverse high and medium scalability innovations in the pipeline, and a favorable ecosystem to expand this work.
The data sets generated during and/or analyzed during this study are available from the corresponding author on reasonable request.
Local community service centers
Groupement Inter-régional de recherche clinique et d’innovation inter-regional grouping for clinical research and innovation
Innovation Scalability Self-Administered Questionnaire
Multi-professional health care center
Soins PRimaires INnovations et Territoires en Occitanie (Primary Care Innovation and Territories In Occitanie)
University multi-professional health care center
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Bonfim D, Belotti L, de Almeida LY, et al. Challenges and strategies for conducting research in primary health care practice: an integrative review. BMC Health Serv Res. 2023;23:1380. https://doi.org/10.1186/s12913-023-10382-1 .
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The authors would like to thank the Occitanie Regional Health Agency and the Faculty of Medicine of Montpellier-Nîmes for funding the Master 2 Research in Epidemiology and Public Health of AV. We would like to thank the study participants for their commitment to this pilot study. We would like to thank the University Departments of General Medicine of Montpellier-Nîmes and Toulouse, as well as FECOP, for their support in distributing this questionnaire. We would like to thank the regional college of teaching generalists in Languedoc Roussillon for its help and involvement in the project.
We would also like to thank the innovation extractor of the Montpellier and Nîmes university hospitals, the Clinical Research and Innovation Delegation of the Montpellier University Hospital Centre, and the Innovations and Partnerships Department of the University of Montpellier for their interest in this study.
We thank all the workteam: Pr Michel Amouyal and Pr Béatrice Lognos from the University Department of General Practice of Montpellier-Nîmes, Dr Christine Delonca from the Clinical Research and Innovation Delegation of the Montpellier University Hospital Centre, Manon Raynal from the FECOP and Mark Oude Engberink from the Avicenne U-PHC.
AV was funded by a research year grant from the Montpellier-Nîmes Faculty of Medicine (University of Montpellier). This grant enables medical residents to carry out a year of research, including a laboratory internship, while being paid as residents.
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Alexis Vandeventer, Grégoire Mercier, Grégory Ninot & François Carbonnel
University Department of General Practice, Faculty of Medicine of Montpellier-Nîmes, University of Montpellier, Montpellier, France
Alexis Vandeventer & François Carbonnel
CHRU Montpellier - Centre Hospitalier Régional Universitaire, Univ Montpellier, Montpellier, France
Grégoire Mercier & Christophe Bonnel
Clinical Research and Epidemiology Unit, CHU Montpellier, Univ Montpellier, Montpellier, France
Joana Pissarra
Maison de santé pluriprofessionnelle universitaire Avicenne, 2 rue Ibn Sinaï dit Avicenne, Cabestany, 66330, France
François Carbonnel
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FC, AV, GM and CB designed the study. AV, FC and GN conducted the study. AV, FC, GM and GN analyzed the data and interpreted the data. AV, FC, GM, GN and CB have drafted the work. JP has substantively revised it. Each author has approved the submitted version and has agreed both to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.
Correspondence to François Carbonnel .
Ethics approval and consent to participate.
Informed consent to participate was obtained as, at the start of the questionnaire, it was indicated that, by filling it, the participants were consenting to participate in this study. The Research Ethics Committee of the University of Montpellier has approved this research project (n°2022–013-bis) (Additional file 5).
The authors declare no competing interests.
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Additional file 1. questions to identify the mhcs and the innovation described. french and english versions., additional file 2. modified issaq questionnaire. french and english versions., additional file 3. cherries checklist., additional file 4. list of identified innovations produced by mhc, by scalability level group., aadditional file 5. research ethics committee of the university of montpellier approval., rights and permissions.
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Vandeventer, A., Mercier, G., Bonnel, C. et al. Identifying innovations produced by primary health care centers and evaluating their scalability: the SPRINT Occitanie cross-sectional study in France. BMC Health Serv Res 24 , 824 (2024). https://doi.org/10.1186/s12913-024-11237-z
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DOI : https://doi.org/10.1186/s12913-024-11237-z
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Resilience is the process and outcome of successfully adapting to difficult or challenging life experiences, especially through mental, emotional, and behavioral flexibility and adjustment to external and internal demands.
A number of factors contribute to how well people adapt to adversities, including the ways in which individuals view and engage with the world, the availability and quality of social resources, and specific coping strategies.
Psychological research demonstrates that the resources and skills associated with resilience can be cultivated and practiced.
Adapted from the APA Dictionary of Psychology
Building your resilience
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New Kid, New Scene
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Trauma, Aging, and Well-Being
Nearly two-thirds of Democrats say President Joe Biden should withdraw from the presidential race and let his party nominate a different candidate, according to a new poll from The Associated Press-NORC Center for Public Affairs Research.
President Joe Biden speaks at a 2024 Prosperity Summit, July 16, 2024, in North Las Vegas, Nevada. (AP Photo/Ronda Churchill, File)
FILE - President Joe Biden speaks at a 2024 Prosperity Summit, July 16, 2024, in North Las Vegas, Nev. Nearly two-thirds of Democrats say President Joe Biden should withdraw from the presidential race and let his party select a different candidate, according to a new poll by the AP-NORC Center for Public Affairs Research. It sharply undercuts his post-debate claim that “average Democrats” are still with him even if some “big names” are turning on him. (AP Photo/Ronda Churchill, File)
Follow AP’s live coverage of the 2024 presidential race.
WASHINGTON (AP) — Nearly two-thirds of Democrats say President Joe Biden should withdraw from the presidential race and let his party nominate a different candidate, according to a new poll, sharply undercutting his post-debate claim that “average Democrats” are still with him even if some “big names” are turning on him.
The new survey by the AP-NORC Center for Public Affairs Research , conducted as Biden works to salvage his candidacy two weeks after his debate flop, also found that only about 3 in 10 Democrats are extremely or very confident that he has the mental capability to serve effectively as president, down slightly from 40% in an AP-NORC poll in February .
The findings underscore the challenges the 81-year-old president faces as he tries to silence calls from within his own party to leave the race and tries to convince Democrats that he’s the best candidate to defeat Donald Trump. The poll was conducted mostly before Saturday’s assassination attempt on Trump at a campaign rally in Pennsylvania. It’s unclear whether the shooting influenced people’s views of Biden, but the small number of poll interviews completed after the shooting provided no early indication that his prospects improved.
Meanwhile, as Vice President Kamala Harris receives additional scrutiny amid the talk about whether Biden should bow out, the poll found that her favorability rating is similar to his — but the share of Americans who have an unfavorable opinion of her is slightly lower.
The poll provides some evidence that Black Democrats are among Biden’s strongest supporters, with roughly half in the survey saying he should continue running, compared to about 3 in 10 white and Hispanic Democrats. Overall, seven in 10 Americans think Biden should drop out, with Democrats only slightly less likely than Republicans and independents to say that he should make way for a new nominee.
“I do have genuine concerns about his ability to hold the office,” said Democrat Andrew Holcomb, 27, of Denver. “I think he’s frankly just too old for the job.”
AP Washington correspondent Sagar Meghani reports a new poll sharply undercuts President Biden’s claim that ‘average Democrats’ are still with him after his debate debacle.
Janie Stapleton, a 50-year-old lifelong Democrat from Walls, Mississippi, held the opposite view, saying Biden is the “best candidate” for president.
People aren’t just sour on Biden on as they size up their choices this election season.
What to know about the 2024 Election
About 6 in 10 Americans want Trump to withdraw -- but relatively few Republicans are in that camp.
As for Biden, younger Democrats are especially likely to want to see him bow out – and to say they’re dissatisfied with him. Three-quarters of Democrats under the age of 45 want Biden to drop out, compared to about 6 in 10 of those who are older.
“I just feel like these two individuals are a sad choice,” said Alexi Mitchell, 35, a civil servant who lives in Virginia. She identifies as a Democratic-leaning independent, and while she thinks Biden is probably still mentally up to the job, she worries that the past few weeks’ unraveling of support makes him a weak candidate, no matter what happens next. “If he doesn’t have control over his own party, that’s a fatal flaw,” she said. “He’s put us in a bad position where Trump might win.”
Despite bullish talk from the Biden campaign heading into the debate, the faceoff only left the president in a deeper hole. Democrats are slightly more likely to say they’re dissatisfied with Biden as their nominee now than they were before his halting performance. About half are dissatisfied, an uptick from about 4 in 10 in an AP-NORC poll from June .
By contrast, most Republicans – about 6 in 10 – came out of the debate very or somewhat satisfied with Trump as their candidate. Too few interviews were conducted after the assassination attempt to provide a clear indication of whether Republicans or Americans overall have rallied further around Trump since then.
David Parrott, a Democrat from Soddy-Daisy, Tennessee, was willing to give Biden the benefit of the doubt given the president’s age, but he still voiced concerns about a potential second term.
“I don’t know if he can make it another four years or not,” said Parrott, a 58-year-old retiree. “Shouldn’t he be sitting at his beach house taking it easy?”
All of the recent churn has left Americans much more likely to think Trump is capable of winning the 2024 election than is Biden – 42% to 18%. About a quarter thought the the two men equally capable of winning.
Even Democrats are relatively dour about their party’s prospects come November.
Only about a third of Democrats believe Biden is more capable of winning than is Trump. About 3 in 10 think the two are equally capable of winning and 16% say victory is more likely to go to the Republican. By contrast, Republicans are overwhelmingly convinced that Trump is in the best position to win.
Trump also has the edge on Biden when Americans consider who is most capable of handling a crisis, 38% to 28%. And people are about equally divided on which candidate has the better vision for the country, with 35% saying Biden and 34% Trump.
For all of the disenchantment Biden is up against, the president insists it’s not too late to turn things around, saying past presidents have come back from a deficit at this stage in the campaign. In an interview Tuesday with BET News , he said many voters haven’t focused yet, adding, “The point is, we’re just getting down to gametime right now.”
The poll did also offer a bright spot for Biden: 40% of adults say he’s more honest than Trump, while about 2 in 10 think the opposite.
Most Democrats — around 6 in 10 — say that Vice President Harris would make a good president, while 22% think not and 2 in 10 don’t know enough to say. The poll showed that 43% of U.S. adults have a favorable opinion of her, while 48% have an unfavorable opinion. Somewhat more have a negative view of Biden: approximately 6 in 10 Americans.
The survey was conducted before Trump selected freshman Sen. JD Vance of Ohio as his running mate. It showed that for most Americans, Vance is still an unknown. Six in 10 don’t know enough about him to form an opinion, while 17% have a favorable view and 22% view him negatively.
The poll of 1,253 adults was conducted July 11-15, 2024, using a sample drawn from NORC’s probability-based AmeriSpeak Panel, which is designed to be representative of the U.S. population. The margin of sampling error for all respondents is plus or minus 3.8 percentage points.
PULLMAN, Wash. – A small 3-ounce sensor capable of recording 2,400 data points of movement in just one second being tested and refined by researchers at Washington State University could be key in reducing the number of injuries to racehorses.
Led by Dr. Warwick Bayly in WSU’s College of Veterinary Medicine, researchers used the biometric sensors, developed by the company StrideSAFE, to track thoroughbreds as they raced and trained at some of the top racetracks in the country. Using collected data, the team was able to identify miniscule stride changes associated with increased risk of injury, allowing intervention before a catastrophic breakdown. The researchers highlighted three horses flagged in 2023 at Churchill Downs in a case study published in the Journal of the American Veterinary Association .
“These racehorses get extensive examinations before races, but catastrophic injuries still happen, and not because they stepped in a hole or took a bad step. A large percentage have a pre-existing pathology not readily apparent on clinical examination,” said Dr. Denise Mc Sweeney, an equine surgery resident at WSU who was the first author on the study. “From our sensor data, we know most catastrophic injuries have a distinct stride pattern. Now we can see when there’s something wrong with their strides and step in before a major injury occurs.”
The sensors measure changes in the rate and direction in which a horse moves its legs and body, and generate graphs of its stride pattern. The data is processed by an algorithm and compared against an “ideal stride” derived from high-performing, sound racehorses. Using data from more than 6,500 starts, the algorithm also identifies similarities with strides produced by horses that suffered catastrophic injuries. Based on how far a stride deviates from ideal and how similar it is to a stride associated with an injury, the horse is assigned an injury risk factor ranging from 1 to 5. Horses with a 5 are 950 times more likely to suffer a catastrophic injury than those with a 1, which is close to the ideal stride. Of the horses tracked, 70% have fallen into category 1, with 3.5% in category 5.
“We know there are about 1.25 catastrophic injuries per 1,000 starts, but identifying those horses before such an event occurs is like finding a needle in a haystack, as they are often subjectively sound during a pre-race examination, and many don’t show any decrease in performance,” Mc Sweeney said. “But if you can narrow it down, like the 3.5% we had out of that group, it is a lot easier to intervene and hopefully prevent injuries.”
To test and refine the algorithm, a sensor was placed on horses starting at Churchill Downs and Ellis Park in Kentucky from April 29 to July 2, 2023. Mc Sweeney was responsible for collecting clinical data on the high-risk horses.
In their case study, the team focused on a pair of 3-year-old colts and a 4-year-old stallion flagged as category 5. In each instance, the sensors alerted veterinarians and trainers to potential injury risks, prompting diagnostic imaging that confirmed an increased risk of catastrophic musculoskeletal injuries. Each horse avoided catastrophic injury after being given time to recover before returning to the track.
“These are prime examples of how this technology can prevent horses from breaking,” Mc Sweeney said. “With this information, the trainers and their vets were able to put the brakes on, and now these horses are going on to have longer careers and, hopefully, avoid a catastrophic injury.”
Mc Sweeney is hopeful the sensors will become standard for all thoroughbred racing and training.
“I believe this is going to make a huge impact,” she said. “The sensors can save the lives of horses and jockeys – they already have.”
WSU has been working with StrideSAFE since 2020 when the sensors were tested at the campus’ Hitchcock Research Racetrack. WSU is the only university in the United States with a dedicated research racetrack. From there the sensors were deployed at Emerald Downs Racetrack in Seattle and have since been used at 10 major tracks across the U.S., including Saratoga, Belmont, Keeneland and Churchill Downs.
The project was supported by a grant from the Kentucky Equine Drug Research Council. In addition to the WSU researchers, co-authors on the study include researchers Dr. Mikael Holmstrom, Kevin Donohue and David Lambert, who are employees and shareholders of StrideSafe. The WSU researchers have no vested interest in the StrideSafe company.
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esearch question for a study, depending on the complex-ity and breadth of your proposed work. Each question should be clear and specific, refer to the problem or phenomenon, reflect an inter. ention in experimental work, and note the target population or participants (see Figure 2.1). Identifying a research question will provide greater focus ...
Hence, a comprehensive review of the topic is imperative, as it allows the researcher to identify this gap in the literature, formulate a hypothesis and develop a research question. To this end, it is crucial to be attentive to new ideas, keep the imagination roaming with reflective attitude, and remain sceptical to the new-gained information ...
Reading regularly is the most common way of identifying a good research question. This enables you to keep up to date with recent advancements and identify certain issues or unsolved problems that keep appearing. Begin by searching for and reading literature in your field. Start with general interest journals, but don't limit yourself to ...
1. Read as much as you can. The answer to how to identify research questions lies in reading the right material and reading extensively. Reading regularly is the most basic way to find a good research question. Keep up to date with recent advancements and identify critical issues or unsolved problems.
Defining the research question is critical first step. Good idea is necessary but not sufficient. Have to convince reviewers that you can accomplish the work; feasible project and team with necessary skills. Know your audience, i.e., match the topic to the funding agency. Data Sharing.
The first question asks for a ready-made solution, and is not focused or researchable. The second question is a clearer comparative question, but note that it may not be practically feasible. For a smaller research project or thesis, it could be narrowed down further to focus on the effectiveness of drunk driving laws in just one or two countries.
A good research question is essential to guide your research paper, dissertation, or thesis. All research questions should be: Focused on a single problem or issue. Researchable using primary and/or secondary sources. Feasible to answer within the timeframe and practical constraints. Specific enough to answer thoroughly.
Identifying the research question. Process of conducting a knowledge synthesis; Constructing a good research question; Inclusion/Exclusion Criteria; ... You should have a draft research question before you choose the type of knowledge synthesis that you will conduct, as the type of answers you are looking for will help guide your choice of ...
Identify your Topic (This is the starting place from where you develop a research question.) Refine by Searching (find background information) (Before you can start to develop a research question, you may need to do some preliminary background research to see (1) what has already been done on the topic and (2) what are the issues surrounding ...
This column is about research questions, the beginning of the researcher's process. For the reader, the question driving the researcher's inquiry is the first place to start when examining the quality of their work because if the question is flawed, the quality of the methods and soundness of the researchers' thinking does not matter. The ...
A brief overview of the research question, approach, results, and interpretation. This is the road map or elevator pitch for an article. Introduction: Several paragraphs (or less) to present the research question and why it is important. A newcomer to the field should get a crash course in the field from this section. Methods: What was done?
Identifying a good researchable question is a process, and in order to develop it, a series of actions and steps is required. Guidelines on research designs and proposals often adopt a linear model, starting with a research question, followed by methods of data collection, analysis, results, discussion, conclusion, and implications.
Identifying a good researchable question is a process, and in order to develop it, a series of actions and steps is required. Guidelines on research designs and proposals often adopt a linear model, starting with a research question, followed by methods of data collection, analysis, results, discussion, conclusion, and implications.
A useful rule-of-thumb for a well-formulated research question is to follow Hulley et al .'s "FINER": feasible, interesting, novel, ethical, and relevant. Manuscript Sections. A research question is a statement that describes the problem that will be studied in the research. It guides the study design and methods for the research.
Explore your topic using your textbooks, reference books, and articles and by consulting with your professor. Be open to tweaking your research question as you gather more information. Watch the videos in this section for advice on developing your research question and considerations related to choosing a topic for which you have a strong opinion.
Good writing begins with clearly stating your research question (or hypothesis) in the Introduction section —the focal point on which your entire paper builds and unfolds in the subsequent Methods, Results, and Discussion sections. This research question or hypothesis that goes into the first section of your research manuscript, the ...
Purpose statements and research questions or hypotheses are interrelated elements of the research process. Research questions are interrogative statements that reflect the problem to be addressed, usually shaped by the goal or objectives of the study (Onwuegbuzie & Leech, 2006).For example, a healthcare article argued that "a good research paper addresses a specific research question.
A research study must: Ask a research question. Identify a research population or group. Describe a research method. Test or measure something. Summarize the results. Research studies are almost always published in peer-reviewed (scholarly) journals. The articles often contain headings similar to these: Literature Review, Method, Results ...
1 Answer to this question. Answer: Typically, manuscripts are divided into the Introduction, Methods, Results, and Discussion sections. This is referred to as the IMRAD structure. The research question, the objective or hypothesis of the study, helps to set up context for what you have researched and why you chose to study this particular topic.
Tip #2: Review state of the art literature. You can only find relevant research topics and questions when you are privy to what the current and relevant research topics and questions are in your field. And, the best way to look for them is through recent and landmark research literature.
When reviewing research that you have found, start by reading the abstract in order to identify the methodologies used in the study. Research articles should also include a section that describes the methods used in more detail. Not all quantitative or qualitative studies will include the same clues present in the examples on this page.
your initial research questions; encyclopedia and other articles used when conducting background research; bibliographies found at the end of books and articles; If you are still struggling, try these suggestions: Use a thesaurus to identify synonyms; Find pictures related to your topic, then describe the picture
Identify the research question: Before writing about research gaps, you need to identify your research question or problem. This will help you to understand the scope of your research and identify areas where additional research is needed. Review the literature: Conduct a thorough review of the literature related to your research question. This ...
Therefore, knowing how to (1) identify popular vs. academic sources, (2) differentiate between primary and secondary sources, and (3) find academic sources is a vital step in writing research. Below are definitions of the two ways scholars categorize types of sources based on when they were created (i.e. time and place) and how (i.e. methodology):
Welcome to Turnitin's new website for guidance! In 2024, we migrated our comprehensive library of guidance from https://help.turnitin.com to this site, guides.turnitin.com. During this process we have taken the opportunity to take a holistic look at our content and how we structure our guides.
Practice-based research is one of the levers identified by the World Health Organization (WHO) to strengthen primary health care. The scaling of health and social care innovations has the potential to reduce inequities in health and to expand the benefits of effective innovations. It is now rapidly gaining the attention of decision-makers in health and social care, particularly in high-income ...
Psychological research demonstrates that the resources and skills associated with resilience can be cultivated and practiced. Adapted from the APA Dictionary of Psychology. Resources from APA. Building your resilience . We all face trauma, adversity, and other stresses. Here's a roadmap for adapting to life-changing situations, and emerging ...
FILE - President Joe Biden speaks at a 2024 Prosperity Summit, July 16, 2024, in North Las Vegas, Nev. Nearly two-thirds of Democrats say President Joe Biden should withdraw from the presidential race and let his party select a different candidate, according to a new poll by the AP-NORC Center for Public Affairs Research.
Using collected data, the team was able to identify miniscule stride changes associated with increased risk of injury, allowing intervention before a catastrophic breakdown. The researchers highlighted three horses flagged in 2023 at Churchill Downs in a case study published in the Journal of the American Veterinary Association.
Police and agencies investigating have been unable to identify a motive so far. Officials briefed on the shooting were told he had visited the site of the attack, the Butler County fairgrounds, at ...