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I would like to ask how systematic reviews/meta-analyses are considered in the academic world. Of course, they are not primary publications, but are they considered more than narrative reviews? That is, publication-wise, are systematic reviews considered a bit less than original data but more than narrative reviews -- thus paying back the additional work required to prepare a systematic analysis over narrative reviews? Thank you.
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Systematic review and meta-analysis occupies the highest position on the pyramid of evidence synthesis. It has got a significant value in the journals.
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I am studying narrative storytelling in deaf children and its relationship to cochlear implant age and oral language acquisition, and I need a task available to assess narrative storytelling
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Between 8 and 12 years old Febini M Joseph
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I can't decide which topic to choose
1- the physics of cancer cells and radiotherapy
2 - electromagnatis in cell regenration
3- a comprehensive review of Nondestructive Spectroscopic Techniques
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I think that the title of the topic(and the topic itself)has to quite clear to the reader. As scientific subject, it is important to give the reader the sense of clear-cut subject, and quite to the point.
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Narrative skills as a tool in medical education
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I have written several papers and books on communication skills in nursing which includes theory of the shift to patient-centred medicine. Approaches that take a humanistic exploration of the person's experience as a basis of relationship-building and diagnosis/assessment are often recommended in specialist fields of care but apply generally to medicine and other clinical practices. For instance, movitational interviewing is based on Carl Rogers' 3 principles of counselling.
I recommend Bensing (2000), paper on 'Bridging the gap: the separate worlds of evidence-based medicine and patient-centred medicine', in Patient Education and Counselling, 39, 17-25. This shows this paradigm shift from a medical approach to a humanistic approach.
Communication skills is now a fundamental skills for nurses in the UK, and is taught in nurse training based on person-centred care. Also see my book 'Communication skills in nursing practice' (2020), published by Sage.
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Can anyone give a detailed explanation on how to write scoping review. I have written narrative review but I don't have complete idea about scoping review. Can someone give me a step by step idea about this with simple explanation. Thanks
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I intend to summarize the guidelines provided by the Joana Briggs Institute for conducting a scoping review.
Step 1 – Define the topic that you will be reviewing; its objectives and any potential sub-questions.
Step 2 – Develop a review protocol. The protocols functions as the plan behind your review. Here you’ll state eligibility criteria (for inclusion/exclusion), how you screened the literature and the charting process that you utilized.
Step 3 – Apply PCC framework
Step 4 – Perform systematic literature searches
Step 5 – Screen the obtained results and only include studies that meet your eligibility criteria
Step 6 – Extract and chart the data you extracted from the collected studies
Step 7 – Write a summary of the evidence to answer your research question(s).
Regards,
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Narratives are methods/methodology and phenomenology is a philosophy. Still, how can they be more clearly differentiated?
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I am currently undertaking a literature review as part of my undergraduate dissertation in which I am synthesising the results from 5 qualitative studies. I was thinking of using either thematic synthesis or narrative synthesis.
What is the difference between thematic synthesis (Thomas and Harden 2008) and thematic analysis? I presumed at first that thematic analysis was only for primary data collection methods, however within narrative synthesis (Popay et al 2006) they state to use thematic analysis if synthesising qualitative data in step 2: 'developing a preliminary synthesis of findings of included studies'.
So, really the question is can I use thematic analysis for a literature review, within the process of narrative synthesis? They don't specify which guidance to use regarding thematic analysis (whether that is Braun and Clarke or another author), so I am a bit stuck. I have found a simplified approach to thematic analysis by Aveyard (2014) in 'Doing a literature review in health and social care: A practical guide' which I would use within narrative synthesis if this is appropriate.
What are everyone's thoughts on this? Advice would be greatly appreciated. Which is more suitable for an undergraduate dissertation: narrative or thematic synthesis?
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Kindly visit the thematic analysis in the RG link.
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Thirteen days from today, I will be defending my PhD. It’s been quite a journey, which I will say more about, eventually. For the time being, I am taking a moment to gather all my strength, energy, and motivation to be ready for this day.
It is important because so much of my life has been dedicated to my research on child maltreatment, trauma and PTSD, depression, resilience, autobiographical narratives and storytelling. Yes, I would like to “pass” this oral exam, but am also looking for ways to enjoy this milestone and not be completely wrecked by stress.
So, I am reaching out for help, since this is something that I struggled with but finally learned to do over the last few years. The Internet is full of tips and tricks but I am looking for advice from friends and people I know, because it’s always nicer and warmer and just more real.
Any tips regarding how to be ready for this, how to deal being a new mom and having this ahead, how to present, what to do, things to avoid, ways to deal with stress or tricky questions (“This is a very interesting question!” has become too cliché), basically, anything that you would like to share is welcome, below or in a private message.
I am also sharing a link to some of my research work below, in case anyone is interested in reading it (and of course, feedback is always welcome): https://www.researchgate.net/profile/Mariam-Fishere
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Sometimes, a doctoral thesis student may have better information than his professors in the field of childhood observation, so trust your little information.
Senior lecturer
Nuha hamid taher
Clinical Psychology
Imam Ja'afar Al-Sadiq University
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I am carrying out a PhD interviewing people who have experienced childhood emotional abuse, I am focussing on how they have navigated a meaningful life into adulthood, how they have coped and how it has affected them in adult life, I have interviewed 16 people using narrative interviews where they have told their life story, I am planning to go back and interview them again using semi structured interviews so I can focus on particular aspects of their narrative. I felt swayed towards IPA and also a phenomenologically informed narrative analysis. I am really keen to get peoples opinions and perspectives on this? Help.....
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Braun and Clarke’s Reflexive Thematic Analysis would be a good fit to what you are describing
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Actually I am looking for any app used by film-editors on the narrative stage , as to visualize narrative, rhythm and pace structure. Structural diagram apps used by film-editors. Or other apps that could be used by film editors even if they are not yet into it.
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ناك العديد من الأدوات المتاحة للمساعدة في بناء القصة . Blake Snyder's Save the Cat.
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Hi all,
I'm currently in the full text review phase of an SLR on predictors / risk factors of treatment resistant depression. I'm including observational studies and RCTs. Virtually all of these studies are non-interventional. For data synthesis, I'm looking to conduct a narrative summary of results, separated in categories such as clinical, genetic, demographic etc. I'm finding it quite difficult to source a risk of bias tool for non-interventional studies with the end product being a narrative summary. Does anyone have any suggestions regarding suitable RoB tools?
Thanks in advance!
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Hi Shane,
For non-interventional studies, I would suggest the Newcastle-Ottawa Scale (NOS) instead of ROB tools because as far as I know ROB tools are mostly used for interventional studies (randomised and non-randomised). This is a link to the Newcastle-Ottawa Scale (NOS): http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.
For interventional studies, I would use ROB tools. I hope this is useful.
Regards,
Reza
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What is the evidence? What aspects must be considered so that we can arrive at such a conclusion? Does that ultimately make the text of the Book of Chronicles different from texts in the DH corpus like Samuel -Kings?
Some notes: Davidic House is one of theological motif (themes) in Chronicles (beside the Temple). Because of the link between DvH and Temple so strong, the Chr expand the narrative about Davidic House in corelation with preparing and building the Temple. So I want to prove that there's indication that Chr sees it from Priestly Perspective and not Prophetic perspective.
Please explain, especially the experts who did research on the book of Chronicles. Your answers at least helped me to structure my research framework. Thank you and God bless
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Sorry outside of my field
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Qualatative research narrative interviews
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I am studying the lived experiences of Black high school seniors and college students concerning their perception of race and gender issues in the school environment, and how they were able to overcome adversity related to issues of race and gender.
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Both the methods ( case study or counter narrative) can be applicable. But may be counter narrative will be more suitable as these arise from the vantage point of those who have been historically marginalized.
You may refer to these articles also:
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Any research on such topic or ideas shared will be appreciated.
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I agree with Marion Todd and Annika Hamachers. Their comments are useful. In addition, David L Morgan lifted up good points about different ways to use narrative analysis. In narrative analysis, it is possible to focus on the content of narratives or on the form of narratives. In the latter, you can consider the different ways people are telling narraives.
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I want to know the complete process of ALP activity experiment for the scaffold using Soas-2. Please reply me as soon as possible. complete narrative way of answer.
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Hi Amit,
You can perform the ALP quantification by using the method describe in this article:
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What are the most influential narratives that fall within the stream of consciousness? And can you tell me some of these stories?
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Agree with Vadim S. Gorshkov
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Have you been curious about the experience of qualitative research participants?
Often when we explore lived experience in qualitative research, participants tell us about some aspects of their life in such a way that they may have never told someone before. When going through such research procedures (like interviews or focused groups) have you been curious about the influence of your designed research procedures on participants' lives? Have you wondered how to do research on the impacts of research participation and the ethical dimensions and issues surrounding such procedures?
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This sounds very interesting Peyman! Of course, participants' experiences of participating in qualitative studies needs to be explored and documented. As a qualitative and narrative inquirer I have engaged with participants with an intention to elicit their stories of lived experiences. I can confirm that they do share with us (researchers) stories they have not shared with anyone else. I think that as qualitative researchers, we have focused on generating data and reporting findings. I like your view which directs us to the perspective of participants.
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Hi,
I'm looking into writing a narrative review around the topic of mental health misinformation on social media and its affect on individuals, but there's barely any studies on this. In this case should i change my topic is or is still possible to write a narrative review?
Thanks in advance!
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This scientific research paper is from The Proceedings of the National Academy of Science in the United States of America and will provide you with abundant information in your academic area of interest!
"COLLOQUIUM PAPER
"Misinformation and public opinion of science and health: Approaches, findings, and future directions"
Michael A. Cacciatore
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PNAS April 13, 2021 118 (15) e1912437117; https://doi.org/10.1073/pnas.1912437117
  1. Edited by Andrew Hoffman, University of Michigan, Ann Arbor, MI, and accepted by Editorial Board Member Susan T. Fiske January 8, 2020 (received for review August 13, 2019)
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Abstract
A summary of the public opinion research on misinformation in the realm of science/health reveals inconsistencies in how the term has been defined and operationalized. A diverse set of methodologies have been employed to study the phenomenon, with virtually all such work identifying misinformation as a cause for concern. While studies completely eliminating misinformation impacts on public opinion are rare, choices around the packaging and delivery of correcting information have shown promise for lessening misinformation effects. Despite a growing number of studies on the topic, there remain many gaps in the literature and opportunities for future studies.
  • misinformation
  • disinformation
  • literature review
The popularity of “misinformation” in the American public consciousness arguably peaked in 2018 during the lead-up to the US midterm elections (1). Shortly after the midterms, “misinformation” was Dictionary.com’s “word of the year” (2), just 1 y after Collins English Dictionary had granted “fake news” the same title (3). Interest was driven largely by a focus on politics and the role that misinformation might have played in influencing candidate preferences and voting behaviors. However, certainly more can be said about a topic that has captured the attention of governments and citizens across the globe. What does “misinformation” (and the terms that are oftentimes treated synonymously) mean? How big of a problem is it in areas outside of politics, including science and health? What do we know about the ways in which it impacts citizens? What can be done to minimize the damage it is doing to public understanding of the key issues of the day?
In this paper I summarize the literature on misinformation with a specific focus on academic studies in areas of science and health. I review the methodological approaches and operationalizations employed in these works, explore the theoretical frameworks that inform much of the misinformation research, and break down the proposed solutions for combatting the problem, including the scholarly research aimed at stopping the spread of such content and lessening its impacts on public opinion. Finally, I discuss avenues for future research. I begin, however, with a discussion of some of the most common definitions of misinformation (and related terms) in the communication literature.
Defining “Misinformation”
An exploration of the literature suggests that “misinformation” is the most commonly employed label for studies focused on the proliferation and impacts of false information. Part of this has to do with the fact that misinformation has become something of a catch-all term for related concepts like disinformation, ignorance, rumor, conspiracy theories, and the like.* Its status as a catch-all term has sometimes resulted in broad use of the concept and imprecise definitions. Much of the earliest work on the topic would employ the label “misinformation” while failing to formally define the concept at all (e.g., refs. 4 and 5), treating misinformation as a known concept.
As misinformation work grew, scholars brought greater structure to the term. Arguably the most commonly applied definition of misinformation is the one offered by Lewandowsky et al. (6), who refer to misinformation as “any piece of information that is initially processed as valid but is subsequently retracted or corrected” (6). Others have removed the “processing” element from this definition, describing misinformation as information that is initially presented as true but later shown to be false (e.g., refs. 7 and 8).
Lewandowsky et al. (9) also draw a line between misinformation and disinformation. While not the first scholars to do so (e.g., ref. 10), their distinction hinges on intentionality, with misinformation operating in the unintentional space and disinformation in the intentional [e.g., “outright false information that is disseminated for propagandistic purposes” (9)]. Nevertheless, studies have continued to lean on the term “misinformation” even when referring to groups who are actively spreading false content for advocacy purposes (e.g., refs. 11 and 12), illustrative of a lingering conceptual fuzziness in the literature.
Ignorance differs from mis/disinformation in terms of both how much an individual knows and the degree of confidence they have in that knowledge. An ignorant person is not only ill-informed but realizes they are, while those who are misinformed are usually confident in their understanding even though it is inaccurate (13, 14). Terms like “myth,” “falsehoods,” and “conspiracy” are less commonly employed and typically serve as synonyms for the more general misinformation.
Methodological Approaches and Operationalizations
This next section will focus on how mis/disinformation has been studied. I will outline five major groupings to this scholarship (content analyses, computational text analysis, network analyses/algorithmic work, public opinion surveys/focus groups/interviews, and experiments) and discuss the common ways mis/disinformation is operationalized and manipulated. I will save the discussion of key conclusions for Trends in the Findings.
Content Analysis.
The goal of virtually all of the content analysis work on mis/disinformation is to diagnose the scope of the problem. Content analyses with some emphasis on mis/disinformation—even if the terms are not specifically acknowledged—have been conducted on a variety of topics, including many health issues.
There is much variation in the mis/disinformation content analysis work, although nearly all this work focuses on online sources. Some have focused on returned internet search results. For example, Hu et al. (15) explored the returned results for skin condition searches on top internet search engines, searching for the relative prevalence of product-focused versus educational websites and the quality of information across those categories of content. Kalk and Pothier (16) took a unique look at information searches online, examining returned Google search results for “schizophrenia” in terms of their readability using the standardized Flesch Reading Ease classification. Rowe et al. (17) focused more narrowly on the open question portal on the BBC website in the immediate aftermath of avian flu’s arriving in the United Kingdom. Their analysis focused not on the potential for online content to misinform the public but on the open question portal as a means of identifying whether and in what areas the public lacked an adequate understanding of avian flu. Still other work has taken a slightly different approach by analyzing the rhetoric and persuasive communication strategies of a specific population to understand what makes their use of disinformation effective (e.g., refs. 18 and 19).
Particularly in the 2010s, content analyses of social media platforms became popular. A collaboration between researchers in Nigeria and Norway looked at the prevalence of medical mis/disinformation in Ebola content shared on Twitter, including a comparison of the potential reach of such content relative to facts (20). Jin et al. (21) also explored Ebola content on Twitter, although with a more narrow focus on rumor spread in the immediate aftermath of news of the first case of Ebola in the United States. Other work has focused on Facebook. Bessi et al. (22, 23) relied on a sample of 1.2 million individuals on the platform to better understand how mainstream scientific and conspiracy news are consumed and shape communities, including correlating user engagement with metrics like numbers of Facebook friends. Content analyses of vaccination-related issues have been conducted on YouTube videos (24, 25), with such work focusing on the stance of the video (positive, negative, or neutral toward vaccines) and false links between vaccines and cases of autism.
Perhaps owing to their oftentimes broader focus on issues outside of mis/disinformation (e.g., the tone of content, the frame being emphasized, etc.), much content analysis work lacks clear operationalizations of mis/disinformation and related measures. The most common operationalizing is a determination of whether the content contains evidence of factually inaccurate information, innuendo, or conspiracy theories (e.g., refs. 11, 19⇓–21, and 26⇓⇓–29). Unfortunately, it is not always clear how the authors are differentiating rumor from fact. Some categorize content by relying solely on assessments by groups of coders who are considered experts in the field (e.g., ref. 30), while others, particularly those in the health communication space, compare content to guidelines put forth by major health organizations like the Centers for Disease Control and Prevention (CDC) or the World Health Organization (e.g., refs. 31 and 32). Still other work is decidedly more subjective in nature, requiring coders to search for any evidence that audiences are struggling with or otherwise made confused or anxious by the content they encounter (e.g., refs. 17 and 33). These more subjective operationalizations reflect the fuzziness around our understanding of mis/disinformation and may serve to overstate the scope of the problem.
Additional work has taken a broader approach to the classification of content, focusing less on specific pieces of communication and more on the source of the information. One approach involves identifying “fake news” pages online and treating all content from those pages as disinformation (e.g., refs. 22, 23, 34, and 35). For example, the Bessi et al.’s (22, 23) studies relied on Facebook pages dedicated to debunking conspiracy theories to identify “conspiracy news pages,” while other work has relied on existing databases and projects that track fake news sources (e.g., refs. 34 and 35). This approach can, of course, be supplemented by then examining the content on these “conspiracy” or “fake news” pages for specific instances of disinformation. A second approach speculates that a misinformed public is likely to follow given the focus of content found online (e.g., ref. 15) or the accessibility/readability of that content (e.g., ref. 16). Rather than explicitly measure mis/disinformation, these works warn that the oftentimes product-focused (rather than health- or education-focused) nature of health websites coupled with the use of jargon and sophisticated language on those pages may breed a misinformed public. Assessments of the conclusions provided by content analyses should therefore be made with these operational decisions in mind since some works may not actually be classifying individual news items, instead deeming all content from a given source as mis/disinformation.
Computational Text Analysis, Natural Language Processing, and Topic Modeling.
A cousin of the content analysis work noted above is the work being done through computational text analysis, natural language processing, and related approaches. While a complete overview of these methodologies is not feasible, one can generally think of these as computer-assisted approaches to the thematic clustering of large-scale textual data. These generally take an inductive approach to data, with computer algorithms identifying topics or themes based on hidden language patterns in texts (36). There are various approaches to the clustering of data and a variety of algorithms used for the task (37), but these computational approaches generally carry with them two key advantages. First, they conduct reliable content analyses on collections of data that are too big to code by hand, and thus are an extension of the content analysis approach noted above. Second, they rely on machine learning, which allows for the discovery of patterns in texts that may not be recognized by individual coders (36).
As one example of this work, Bousallis and Coan (38) retrieved all climate change-focused documents produced by 19 well-known conservative think tanks and classified them by type and theme using a clustering algorithm. This approach allowed the authors to identify, among other things, a misinformation campaign that escalated over a 15-y period between 2008 and 2013. Other work in this space uses these methodologies in concert with various forms of metadata or existing datasets. For instance, Farrell (39) collected philanthropic data, including lists of conference attendees and speakers, and combined this information with existing datasets of all persons known to be connected to organizations linked to the promulgation of climate change misinformation between 1993 and 2017. Using natural language processing, he was able to identify the degree to which persons and organizations linked to climate mis/disinformation were also integrated into mainstream philanthropic networks. He also took a similar approach to the question of corporate funding, combining Internal Revenue Service data of Exxon Mobile and Koch Industries funding donations with collections of government documents and written and verbal texts from both mainstream news media and groups opposing the science of climate change (40). Relying on a combination of network science and machine-learning text analysis, this work was able to not only explain the corporate structure of the climate change countermovement but also pinpoint its influence on mainstream news media and politics.
Network Analysis, Algorithms, and Online Tracking.
At the same time that the work identified above was identifying the scope of the mis/disinformation problem, efforts were being made, largely through computer technology, to help solve it. A first step in this process—the identification of factually inaccurate information from legitimate news—has become attractive to scholars working in artificial intelligence and natural language processing. Vosoughi et al. (41) focused on identifying the salient features of rumors by examining their linguistic style, the characteristics of the people who share them, and network propagation dynamics. Other work has focused on specific features of content, like hashtags, links, and mentions (42).
Once rumors and false content are identified, the next step is controlling or stifling their spread. Rumor control studies can be grouped into two major categories. First, scholars have focused on garnering a general understanding of how information—factual or otherwise—is shared and spread online (e.g., refs. 23, 32, 35, 43, and 44). This work looks at the structure of online communities, including the strength of ties between community members and key features of information sources, like whether a source of content is likely a bot. Patterns in shared content are examined, as well, including key features of messages that garner engagement and time series models to better understand the speed at which information is shared. Bessi et al. (23), for example, focused on homophily and polarization as key triggers in the spread of conspiracies, while Jang et al. (44) focused on the differences in authorship between fake and real news and the alterations that each go through as they are shared online.
The second major approach to rumor control work focuses on identifying critical nodes in social networks and either removing them from the network or combatting their effects via information cascades. These works focus heavily on building and testing algorithms that can be automatically applied to large-scale data so as to identify and deal with critical nodes both quickly and at low costs. As one example, a group of researchers looked at information cascades as a method for limiting the spread of mis/disinformation (45). Their approach focuses on stifling the spread of false information by identifying it early, seeding key nodes in a social network with accurate information, and allowing those users to spread the accurate information to others before they are exposed to the false content.
The operationalization of mis/disinformation in these works generally follows that noted for content analyses. In fact, work in this area often includes a content analysis component for identifying mis/disinformation and the major sources of such content. Once mis/disinformation has been identified the authors model the information and run simulations on the data.
Public Opinion Surveys/Focus Groups/Interviews.
Surveys and focus groups are popular for understanding how different population groups perceive or are vulnerable to the problems of mis/disinformation. Studies of expert populations are common in the space of healthcare and disease. For example, Ahmad et al. (46) conducted focus groups with physicians to learn more about the benefits and risks of incorporating internet-based health information into routine medical consultations. A similar approach was taken by Dilley et al. (47), who employed surveys and structured interviews with physicians and clinical staff to learn more about the barriers to human papillomavirus vaccination.
The bulk of survey, focus group, and interview work in this area, however, has focused on lay audiences. Nyhan (13) focused on public misperceptions in the context of healthcare reform, relying on secondary survey data to show how false statements about reform by politicians and media members were linked to misperceptions among American audiences. Silver and Matthews (48) relied on semistructured interviews with survivors of a tornado to learn more about the spread of (mis)information in the aftermath of a disaster, while Kalichman et al. (49) surveyed over 300 people living with HIV/AIDS to assess their vulnerability to medical mis/disinformation.
Mis/disinformation is generally operationalized in similar ways in surveys, focus groups, and interviews. The work with expert populations will often employ attitudinal measures to understand how experts view the size of the problem within a given topic area (e.g., refs. 46, 47, 50, and 51). The work with lay audiences will more often employ measures of factual knowledge—for example, true/false items about the causes, symptoms, and possible cures for a given disease or virus (12, 52⇓–54)—or perceived knowledge or concerns (e.g., refs. 53 and 55), which might ask respondents to report how much they believe they know about a topic, or how big a problem they believe inaccurate information to be. Other work has utilized quasi-experimental stimuli to assess a respondent’s susceptibility to false content by exposing participants to different-quality webpages before asking them to rate the pages in terms of believability and trust (49). Finally, attempts have been made to distinguish mere ignorance from actual mis/disinformation by analyzing not only whether an individual holds a misperception but how strongly that misperception is tied to their self-assessed knowledge of the topic (13).
Experiments.
With the possible exception of content analysis work, experiments have been the most popular methodological approach to the issue of mis/disinformation. It is worth noting that most experiments have tended to focus on misinformation in the form of honest journalist or witness mistakes, rather than more flagrant attempts to deceive (i.e., disinformation). Much of this work has explored the role of retractions or corrections in lessening the continued influence of misinformation in the minds of the public, but other approaches have been employed, including inoculating people to misinformation prior to exposure (e.g., refs. 56 and 57), providing participants with myth–fact sheets or event statements that correct the misinformation (58⇓–60), and using the “related links” feature on Facebook, or subsequent posts in a social media newsfeed, to provide alternative viewpoints on the topic (61⇓–63).
Some work has avoided the use of retractions or inoculating information altogether by looking at intervention materials for areas where misperceptions are already common, such as vaccines (64). Still other work falls outside this general framework. Rather than attempting to reverse misperceptions in people’s minds, Nyhan and Reifler (65) used a mailed reminder of fact-checking services to see if the reminder would deter politicians from making false statements on the campaign trail.
Experimental work generally operationalizes mis/disinformation in one of several ways. First, it is oftentimes a manipulated variable, with the most common manipulations taking the form of providing a false piece of information to experimental participants. These are typically real or constructed news articles or “dispatches” (e.g., refs. 66 and 67) but might also be brief posts or headlines shared on social media (e.g., ref. 68), generic statements or statistics (e.g., refs. 60 and 69), quotes from a politician (e.g., ref. 70), or recordings of news reports (e.g., ref. 71). After exposure, participants will receive some form of retraction notice, thus turning the original information into misinformation.
Misperceptions are typically assessed after exposure to an experimental stimulus through some form of factual knowledge questions, attitudinal items, or inference queries. Factual knowledge questions might take the form of basic fact-recall items based on information in the communication to which the participant was exposed (e.g., “On which day did the accident occur?”; ref. 58). These are similar to the measures employed in survey work, and might take the form of true–false items. Some work assesses fact-recall with response booklets, where participants are asked to provide as many event-related details as possible to provide a complete account of the event (e.g., ref. 58).
Attitudinal items are usually posed around the key components of the shared mis/disinformation. For instance, a study about the false link between vaccines and autism first presented participants with misinformation then corrected that information in one of several ways before measuring attitudes related to the misinformation through a series of agree–disagree items (e.g., “Some vaccines cause autism in healthy children” or “If I have a child, I will vaccinate him or her”; ref. 61).
Inference questions are generally open-ended and allow a respondent to either reference the inaccurate content they were originally given, reference the correction to that information, or avoid the context altogether. In their study of a fictitious minibus accident, Ecker et al. (58) asked participants the following inference question: “Why do you think it was difficult getting both the injured and uninjured passengers out of the minibus?” Having first misinformed participants by noting that the passengers were elderly, and then later correcting that information, a reference to the advanced age of the passengers would be evidence of misinformation.
Finally, unique approaches to studying mis/disinformation require unique approaches to measuring outcomes. The Nyhan and Reifler (65) study that used a reminder of fact-checking to see if it deterred politicians from making false statements measured how dishonest the politicians were in their later statements by turning to PolitiFact ratings and searching LexisNexis for any media articles that challenged a statement by any of the legislators in the study.
Theoretical Underpinnings
The Continued Influence Effect.
The backbone of a significant number of studies of mis/disinformation, particularly many of the experimental approaches built around correcting the effects of misinformation on the public, is the so-called continued influence effect (CIE). The CIE refers to the tendency for information that is initially presented as true, but later revealed to be false, to continue to affect memory and reasoning (59). A relatively small group of researchers have made the most headway in this space, primarily exploring the CIE in news retraction and correction studies (e.g., refs. 6, 58⇓–60, 66, 67, and 71⇓–73).
There are multiple proposed explanations for the CIE. The first concerns “mental event models” (74, 75). People are said to build mental models of events as they unfold. However, in doing so, they are reluctant to dismiss key information, such as the cause of an event, unless a plausible alternative exists to replace the dismissed information. If no plausible alternative is available, people prefer an inconsistent model over an incomplete one, resulting in a continued reliance on the outdated information.
The second explanation for the CIE is focused on retrieval failure in controlled memory processes (6). This process can be relatively simple, such as misattributing a specific piece of information to the wrong source (e.g., recalling the subsequently retracted cause of a fire but thinking that information came from the credible police report), or it might be rather complex, having to do with dual-process theory and the automatic versus strategic retrieval of information from memory (76). While a complete overview of dual-process theory is beyond the scope of this paper, this explanation largely focuses on a breakdown in the encoding and retrieval process in memory due to things like time pressure or cognitive overload (73). In short, how we encode information impacts how quickly and with what accuracy we will retrieve information at a later time.
A third explanation for the CIE concerns processing fluency and familiarity. Oftentimes, in producing a retraction we repeat the initial false information, which may inadvertently increase the strength of that information in the receiver’s memory and their belief in it by making it more familiar (73). When the receiver is later called upon to recall the event, the mis/disinformation is more easily recalled, thereby giving it greater credence. Finally, there is some evidence that the CIE might be based on reactance effects, whereby people do not like being told what to think and push back when they are told to disregard an earlier piece of information by a retraction. This explanation has been largely tested in courtroom settings where jurors are asked to disregard a piece of evidence after being told it is inadmissible (6).
Motivated Reasoning.
Since at least the mid-20th century, scholars have noted that partisans are selective in both their choice and processing of information. The biased processing of content has come to be known as “motivated reasoning.” Motivated reasoning has become a popular concept in mis/disinformation research, particularly for issues with a strong partisan divide (e.g., refs. 13, 61, 66, 72, and 77).
Several mechanisms have been proposed to explain motivated reasoning, including the prior attitude effect, disconfirmation bias, and confirmation bias (78). The prior attitude effect occurs when “people who feel strongly about an issue … evaluate supportive arguments as stronger and more compelling than opposing arguments” (78). Disconfirmation bias argues that “people will spend more time and cognitive resources denigrating and counterarguing attitudinally incongruent than congruent arguments” (78). Individuals are engaging in confirmation bias when they choose to expose themselves to “confirming over disconfirming arguments” when they are given freedom in their information choice (78). Additional work has expanded upon the mechanisms noted here. For instance, Jacobson’s (79) selective perception argues that “people are more likely to get the message right when it is consistent with prior beliefs and more likely to miss it when it is not” (79), while his selective memory suggests that “people are more likely to remember things that are consistent with current attitudes and to forget or misremember things that are inconsistent with them” (79). In the context of mis/disinformation, motivated reasoning can help explain why some people may be resistant to new information that, for example, contradicts a believed link between vaccinations and autism (64).
Other Concepts Common to the Literature.
Factors related to the CIE and motivated reasoning that are also common in the mis/disinformation literature include echo chambers (“polarized groups of like-minded people who keep framing and reinforcing a shared narrative”; ref. 80), filter bubbles (“where online content is controlled by algorithms reflecting user’s prior choices”; ref. 44), worldviews (audience values and orientation toward the world, including their political ideology; ref. 6), and skepticism (the degree to which people question or distrust new information or information sources; ref. 6). These concepts generally help explain the resistance to correcting information that forms the foundation of the CIE.
Trends in the Findings
How Big Is the Problem?
As noted, content analysis work and computational text analyses have helped scholars better understand the scope of the mis/disinformation problem. A complete summary of the studies in this space is not feasible; however, some patterns are worth noting. First, there is often convergence in results even with vastly different approaches to studying the problem. The work on vaccine mis/disinformation represents one area where scholars have generally coalesced in their research findings. For example, Basch et al. (24) explored videos about vaccines on YouTube and found that a strong percentage reported a link between vaccines and autism, a finding that was echoed by Donzelli et al. (25) in their exploration of the same topic and platform. Those findings have been complemented by Moran et al. (19) and Panatto et al. (11), who identified similar false claims about links between vaccination and autism and Gulf War syndrome, respectively, in their samples of web pages. Computational analyses focused on climate change communication have also generally identified problems with mis/disinformation. For example, Boussalis and Coan (38) found increases in climate change mis/disinformation over time, arguing that the “era of science denial” is alive and well, while Farrell (36) found evidence that organizations that produce climate contrarian texts exert strong influence within networks and therefore wield great power in the spread of information.
At the same time, results have not always been consistent, even when exploring the same issue within the same medium. For instance, researchers conducted a search of “Ebola” and “prevention” or “cure” on Twitter, a search that returned a large set of tweets, of which 55% were said to contain medical mis/disinformation with a potential audience of more than 15 million (as compared to about 5.5 million for the medically accurate tweets) (20). Also on Twitter, Jin et al. (21) looked at rumor spread in the immediate aftermath of news of the first case of Ebola in the United States. They found rumors to represent a relatively small fraction of the overall Ebola-related content on the platform. They also found evidence that rumors typically remain more localized and are less believed than legitimate news stories on the topic. All told, the work focused on identifying the scope of the mis/disinformation problem, while oftentimes varying in approach, has consistently found evidence for at least some degree of concern, although pinpointing the exact nature of the problem has proven difficult.
Combatting the Spread of Misinformation.
Computational analyses, including algorithm creation, have allowed for a better understanding of how mis/disinformation spreads, particularly in the online environment. This work is promising for alerting people to likely pieces of false content and has potential for limiting its spread. Vosoughi et al. (41) focused on mis/disinformation identification. They explored the linguistic style of rumors, the characteristics of the people who share them, and network propagation dynamics to develop a model for the automated verification of rumors. They tested their system on 209 rumors across nearly 1 million tweets and found they were able to correctly predict 75% of the rumors, and did so faster than any other public source. Similarly, Ratkiewicz et al. (42) created the “Truthy” system, which identified misleading political memes on Twitter through tweet features like hashtags, links, and mentions.
The work on rumor control has also yielded important findings. Pham et al. (81) developed an algorithm for identifying a set of nodes in a social network that, if removed, will severely limit the spread of mis/disinformation. The authors claim that their approach is not only efficient but a cost-effective tool for combatting mis/disinformation spread. Similar algorithms have been developed by Saxena et al. (82) and Zhang et al. (83). In each case, the authors argue that their algorithmic approach can dramatically disrupt information spread, preventing exposure to a large number of nodes. Of course, the question with these works, and others not outlined here, is how nodes will ultimately be removed from a network, and under what circumstances it is ethically and legally feasible to remove or silence a social media user.
Perhaps because of these questions, Tong et al. (45) focused on stifling the spread of mis/disinformation by identifying it early, seeding key nodes in a social network with accurate information, and allowing those users to spread the accurate information to others before exposure to the false content. Their approach was found effective for rumor blocking, suggesting there are multiple promising avenues for identifying and controlling the spread of mis/disinformation online.
Combatting Misinformation within Members of the Public.
Arguably the most extensive work aimed at combatting misinformation is the experimental work on retractions and corrections, usually in the context of the CIE. Once again, this work has generally focused on honest mistakes in reporting rather than more deliberate attempts to deceive, which is likely to impact how receptive audiences are to correcting information. Work in this space has focused on altering the impact of a retraction by being more clear and direct with its wording (74), repeating it multiple times (84), altering the timeline for the presentation of the retraction (74, 85), and providing supplemental information alongside it (i.e., giving reasons why the misinformation was first assumed to be factual; ref. 86). Other work has focused on the emotionality of the misinformation (87) or has manipulated how carefully a respondent is asked to attend to the presented information (88).
Virtually no work has been successful at completely eliminating the effects of misinformation; however, some studies have shown promise for reducing misperceptions. Among the most promising involves delivering warnings at the time of initial exposure to the misinformation (6). Ecker et al. (58) found that a highly specific warning (a detailed description of the CIE) reduced but failed to fully eliminate the CIE. A more general warning having to do with the limitations of fact checking in media did very little to reduce reliance on misinformation. Cook et al. (56), as well as van der Linden et al. (57), have found promising evidence that audiences can be inoculated against the effects of false content by providing very specific warnings about issues like false-balance reporting and the use of “fake experts.” It is worth noting that warnings are most effective when they are administered prior to mis/disinformation exposure (89).
The repetition or strengthening of retractions has been found to reduce, but again not eliminate, the CIE (6). The best evidence of this is from a study by Ecker et al. (73), who varied both the strength of the misinformation (one or three repetitions) and the strength of the retractions (zero, one, or three repetitions). Their experiments revealed that after three presentations of misinformation a single retraction served to lessen reliance on misinformation, with three retractions reducing it even further. However, the repetition of misinformation also had a stronger effect on thinking than the repetition of the retraction (73). Therefore, efforts to correct a misperception through repetition of a retraction might actually result in boomerang effects as retractions oftentimes involve repeating the original misinformation (90). Further, there is at least some evidence that the repetition of a retraction produces a “protest-too-much” effect, causing message recipients to lose confidence in the retraction (86).
The provision of alternative narratives has also shown promise for reducing the CIE. An alternative narrative fills the gap in a recipient’s mind when a key piece of evidence is retracted (e.g., “It wasn’t the oil and gas [that caused the fire], but what else could it be?”; ref. 6). There is some fMRI data that corroborates this theory as it found that the continued influence of retracted information may be due to a breakdown of narrative-level integration and coherence-building mechanisms implemented by the brain (71). To maximize effectiveness, the alternative narrative should be plausible, should account for the information that was removed by the retraction, and should explain why the misinformation was believed to be correct (6).
Other factors that have been tested include recency and primacy effects, with recency emerging as a more important contributor to the persistence of misinformation as people generally rely more on recent information in their evaluations of retractions (59). Familiarity and levels of explanatory detail have also been tested (60). The authors found that providing greater levels of detail when correcting a myth produced a more sustained change in belief. They also found that the affirmation of facts worked better than the retraction of myths over the short term (1 wk), but not over a longer term (3 wk), and that this effect was most pronounced among older rather than younger adults. It is also worth noting that combining approaches can enhance their effects. For example, merging a specific warning with a plausible alternative explanation can further reduce the CIE compared with administering either of those approaches separately (58).
Source work has also been popular for combatting the effects of false information. For instance, having the refutation of a rumor come from an unlikely source, such as someone for whom the refutation runs counter to their personal or political interests, can increase the willingness of even partisan individuals to reject the rumor (66). It is worth noting, however, that the author conducted a content analysis of rumor refutation by unlikely sources in the context of healthcare reform and found it to be an exceedingly rare event.
Driven by its role in the proliferation of mis/disinformation, Bode and Vraga (61) have focused their correction studies on social media. One study did so using the “related stories” function on Facebook. This work presented participants a Facebook post that contained inaccurate content and then manipulated the related stories around it to either 1) confirm, 2) correct, or 3) both confirm and correct that information. The analysis revealed a significant reduction in misperceptions among those participants who received content designed to correct it. They later looked at source credibility in the context of information shared on Twitter and found that while a single correction from another social media user failed to significantly reduce misperceptions, a single correction from the CDC could impact misperceptions (62). In fact, corrections from the CDC worked best among those with the highest levels of initial misperception. They further investigated whether providing a source was necessary to curb misperceptions by having two individual commenters discredit the information in a Facebook and Twitter conversation (68). In one condition those users provided a link to debunking news stories from the CDC or Snopes.com, while in the other they did so without reference to any outside sources. Their results suggest a source is needed to correct misperceptions.
Finally, outside of factors related to the misinformation itself or the retraction, individual-level differences have also been tested in the context of the CIE and misinformation correction studies, including racial prejudice (72), worldview and partisanship (70, 91), and skepticism (92), with mixed results scattered across studies.
Gaps in the Literature and Moving Forward
While misinformation remains a relatively new topic of public concern, scholars have been addressing issues in this space for quite some time. The result is a large body of literature, but one with significant gaps. Perhaps most worrisome is that much of the work has focused on combatting misinformation, and, importantly, not disinformation. This distinction is subtle, but important. The bulk of the studies focused on the CIE, for instance, have focused on small journalistic errors in reporting (e.g., misrepresenting the cause of a fire) and have largely avoided issues characterized by more deliberate attempts to deceive and persuade. Of course, the major controversy surrounding false information has less to do with honest errors in writing and much more to do with deliberate attempts to deceive. The early retraction studies (e.g., refs. 58 and 87) have provided a strong foundation of initial findings, but we must push these further with highly partisan issues and audiences.
Related to the point above, relatively few studies have explored methods for inoculating individuals from mis/disinformation. As noted, progress has been made in this space with regard to issuing warnings about things like the CIE prior to misinformation exposure (58). Other work has explored factors like false-balance reporting and the use of “fake experts,” also with promising results (56, 57). While such work does not always completely prevent mis/disinformation from taking hold, it does present a promising avenue for better understanding the causes of mis/disinformation and ways to prevent its spread.
A third gap in the literature, one articulated by Lewandowsky et al. (6), has to do with the relative dearth of studies focused on individual-level differences that exacerbate or attenuate things like the CIE. The authors specifically reference intelligence, memory capacity and updating abilities, and tolerance for ambiguity as factors worthy of research attention. However, other factors, including elaborative processing, social monitoring, and a host of variables related to media use and literacy, also remain untested. Greater attention should also be paid to the role of emotion in both the processing of mis/disinformation and its spread (6).
A fourth gap in the literature has to do with better understanding the mechanisms that explain the persistence of mis/disinformation in our minds. Different pathways have been suggested for explaining why mis/disinformation is so difficult to combat. However, relatively few studies have attempted to test competing theories, instead choosing to speculate on explanations post hoc. The functional MRI work of Gordon et al. (71) is both an interesting approach and promising step in furthering our understanding of information persistence. Without more definitive attempts to explain the process through which mis/disinformation seemingly infects our brains, we are doomed to continue the uphill battle against this content.
A common thread in much of the literature cited in this paper is a focus on individuals—typically everyday citizens—and their perceptions. Of course, mis/disinformation can also influence other populations, including political elites, the media, and funding organizations. Indeed, it is arguably most impactful when these audiences are reached as they represent potentially powerful pathways to political influence. Unfortunately, there is a relative dearth of work in this space, at least as compared to studies focused on individual perceptions. Notable exceptions can be found in some of the computational work focused on climate change countermovements (e.g., refs. 36 and 38⇓–40). For example, Brulle (93) recently examined the network of political coalitions, including those in coal and oil and gas sectors, to better understand the organization and structure of a movement opposed to mandatory limits on carbon emissions. Further work focused on the nature and makeup of networks involved in the spread of false content is an especially fruitful path for future research.
Finally, it is worth noting that addressing any of the above gaps in the literature will be very difficult without paying greater attention to issues of conceptualization and operationalization that plague many of the key concepts in the space. Far too many studies have defined or measured misinformation in ways that are actually reflective of different concepts, including disinformation, ignorance, or misunderstandings. A necessary first step in improving our understanding of mis/disinformation impacts and combatting their negative effects, therefore, is to clearly and appropriately define what we mean by key terms and how we should be measuring them in empirical studies of the topic.
Data Availability Statement.
There are no data associated with the paper.
Footnotes
  • ↵1Email: mcacciat@uga.edu.
  • Author contributions: M.A.C. performed research and wrote the paper.
  • The author declares no competing interest.
  • This paper results from the Arthur M. Sackler Colloquium of the National Academy of Sciences, “Advancing the Science and Practice of Science Communication: Misinformation About Science in the Public Sphere,” held April 3–4, 2019, at the Arnold and Mabel Beckman Center of the National Academies of Sciences and Engineering in Irvine, CA. NAS colloquia began in 1991 and have been published in PNAS since 1995. From February 2001 through May 2019, colloquia were supported by a generous gift from The Dame Jillian and Dr. Arthur M. Sackler Foundation for the Arts, Sciences, & Humanities, in memory of Dame Sackler’s husband, Arthur M. Sackler. The complete program and video recordings of most presentations are available on the NAS website at http://www.nasonline.org/misinformation_about_science.
  • This article is a PNAS Direct Submission. A.H. is a guest editor invited by the Editorial Board.
  • ↵*I will often employ the general label “mis/disinformation” in this work when referring to literatures or studies that are ambiguous or especially broad in their focus. I will reserve more specific terms like “disinformation” or “rumor” for use when discussing those specific studies that use that language.
Published under the PNAS license.
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d—have been conducted on a variety of topics, including many health issues.
There is much variation in the mis/disinformation content analysis work, although nof coders who are considered experts in the field (e.g., ref. 30), while others, particularly those in the health communication space, compare content to guidelines put forth by major health organizations like the Centers for Disease Control and Prevention (CDC) or the World Health Organization (e.g., refs. 31 and 32). Still other work is decidedly more subjective in nature, requiring coders to search for any evidence that audiences are struggling with or otherwise made confused or anxious by the content they encounter (e.g., refs. 17 and 33). These more subjective operationalizations reflect the fuzziness around our understanding of mis/disinformation and may serve to overstate the scope of the problem.
Additional work has taken a broader approach to the classification of content, focusing less on specific pieces of communication and more on the source of the information. One approach involves identifying “fake news” pages online and treating all content from those pages as disinformation (e.g., refs. 22, 23, 34, and 35). For example, the Bessi et al.’s (22, 23) studies relied on Facebook pages dedicated to debunking conspiracy theories to identify “conspiracy news pages,” while other work has relied on existing databases and projects that track fake news sources (e.g., refs. 34 and 35). This approach can, of course, be supplemented by then examining the content on these “conspiracy” or “fake news” pages for specific instances of disinformation. A second approach speculates that a misinformed public is likely to follow given the focus of content found online (e.g., ref. 15) or the accessibility/readability of that content (e.g., ref. 16). Rather than explicitly measure mis/disinformation, these works warn that the oftentimes product-focused (rather than health- or education-focused) nature of health websites coupled with the use of jargon and sophisticated language on those pages may breed a misinformed public. Assessments of the conclusions provided by content analyses should therefore be made with these operational decisions in mind since some works may not actually be classifying individual news items, instead deeming all content from a given source as mis/disinformation.
Computational Text Analysis, Natural Language Processing, and Topic Modeling.
A cousin of the content analysis work noted above is the work being done through computational text analysis, natural language processing, and related approaches. While a complete overview of these methodologies is not feasible, one can generally think of these as computer-assisted approaches to the thematic clustering of large-scale textual data. These generally take an inductive approach to data, with computer algorithms identifying topics or themes based on hidden language patterns in texts (36). There are various approaches to the clustering of data and a variety of algorithms used for the task (37), but these computational approaches generally carry with them two key advantages. First, they conduct reliable content analyses on collections of data that are too big to code by hand, and thus are an extension of the content analysis approach noted above. Second, they rely on machine learning, which allows for the discovery of patterns in texts that may not be recognized by individual coders (36).
As one example of this work, Bousallis and Coan (38) retrieved all climate change-focused documents produced by 19 well-known conservative think tanks and classified them by type and theme using a clustering algorithm. This approach allowed the authors to identify, among other things, a misinformation campaign that escalated over a 15-y period between 2008 and 2013. Other work in this space uses these methodologies in concert with various forms of metadata or existing datasets. For instance, Farrell (39) collected philanthropic data, including lists of conference attendees and speakers, and combined this information with existing datasets of all persons known to be connected to organizations linked to the promulgation of climate change misinformation between 1993 and 2017. Using natural language processing, he was able to identify the degree to which persons and organizations linked to climate mis/disinformation were also integrated into mainstream philanthropic networks. He also took a similar approach to the question of corporate funding, combining Internal Revenue Service data of Exxon Mobile and Koch Industries funding donations with collections of government documents and written and verbal texts from both mainstream news media and groups opposing the science of climate change (40). Relying on a combination of network science and machine-learning text analysis, this work was able to not only explain the corporate structure of the climate change countermovement but also pinpoint its influence on mainstream news media and politics.
Network Analysis, Algorithms, and Online Tracking.
At the same time that the work identified above was identifying the scope of the mis/disinformation problem, efforts were being made, largely through computer technology, to help solve it. A first step in this process—the identification of factually inaccurate information from legitimate news—has become attractive to scholars working in artificial intelligence and natural language processing. Vosoughi et al. (41) focused on identifying the salient features of rumors by examining their linguistic style, the characteristics of the people who share them, and network propagation dynamics. Other work has focused on specific features of content, like hashtags, links, and mentions (42).
Once rumors and false content are identified, the next step is controlling or stifling their spread. Rumor control studies can be grouped into two major categories. First, scholars have focused on garnering a general understanding of how information—factual or otherwise—is shared and spread online (e.g., refs. 23, 32, 35, 43, and 44). This work looks at the structure of online communities, including the strength of ties between community members and key features of information sources, like whether a source of content is likely a bot. Patterns in shared content are examined, as well, including key features of messages that garner engagement and time series models to better understand the speed at which information is shared. Bessi et al. (23), for example, focused on homophily and polarization as key triggers in the spread of conspiracies, while Jang et al. (44) focused on the differences in authorship between fake and real news and the alterations that each go through as they are shared online.
The second major approach to rumor control work focuses on identifying critical nodes in social networks and either removing them from the network or combatting their effects via information cascades. These works focus heavily on building and testing algorithms that can be automatically applied to large-scale data so as to identify and deal with critical nodes both quickly and at low costs. As one example, a group of researchers looked at information cascades as a method for limiting the spread of mis/disinformation (45). Their approach focuses on stifling the spread of false information by identifying it early, seeding key nodes in a social network with accurate information, and allowing those users to spread the accurate information to others before they are exposed to the false content.
The operationalization of mis/disinformation in these works generally follows that noted for content analyses. In fact, work in this area often includes a content analysis component for identifying mis/disinformation and the major sources of such content. Once mis/disinformation has been identified the authors model the information and run simulations on the data.
Public Opinion Surveys/Focus Groups/Interviews.
Surveys and focus groups are popular for understanding how different population groups perceive or are vulnerable to the problems of mis/disinformation. Studies of expert populations are common in the space of healthcare and disease. For example, Ahmad et al. (46) conducted focus groups with physicians to learn more about the benefits and risks of incorporating internet-based health information into routine medical consultations. A similar approach was taken by Dilley et al. (47), who employed surveys and structured interviews with physicians and clinical staff to learn more about the barriers to human papillomavirus vaccination.
The bulk of survey, focus group, and interview work in this area, however, has focused on lay audiences. Nyhan (13) focused on public misperceptions in the context of healthcare reform, relying on secondary survey data to show how false statements about reform by politicians and media members were linked to misperceptions among American audiences. Silver and Matthews (48) relied on semistructured interviews with survivors of a tornado to learn more about the spread of (mis)information in the aftermath of a disaster, while Kalichman et al. (49) surveyed over 300 people living with HIV/AIDS to assess their vulnerability to medical mis/disinformation.
Mis/disinformation is generally operationalized in similar ways in surveys, focus groups, and interviews. The work with expert populations will often employ attitudinal measures to understand how experts view the size of the problem within a given topic area (e.g., refs. 46, 47, 50, and 51). The work with lay audiences will more often employ measures of factual knowledge—for example, true/false items about the causes, symptoms, and possible cures for a given disease or virus (12, 52⇓–54)—or perceived knowledge or concerns (e.g., refs. 53 and 55), which might ask respondents to report how much they believe they know about a topic, or how big a problem they believe inaccurate information to be. Other work has utilized quasi-experimental stimuli to assess a respondent’s susceptibility to false content by exposing participants to different-quality webpages before asking them to rate the pages in terms of believability and trust (49). Finally, attempts have been made to distinguish mere ignorance from actual mis/disinformation by analyzing not only whether an individual holds a misperception but how strongly that misperception is tied to their self-assessed knowledge of the topic (13).
Experiments.
With the possible exception of content analysis work, experiments have been the most popular methodological approach to the issue of mis/disinformation. It is worth noting that most experiments have tended to focus on misinformation in the form of honest journalist or witness mistakes, rather than more flagrant attempts to deceive (i.e., disinformation). Much of this work has explored the role of retractions or corrections in lessening the continued influence of misinformation in the minds of the public, but other approaches have been employed, including inoculating people to misinformation prior to exposure (e.g., refs. 56 and 57), providing participants with myth–fact sheets or event statements that correct the misinformation (58⇓–60), and using the “related links” feature on Facebook, or subsequent posts in a social media newsfeed, to provide alternative viewpoints on the topic (61⇓–63).
Some work has avoided the use of retractions or inoculating information altogether by looking at intervention materials for areas where misperceptions are already common, such as vaccines (64). Still other work falls outside this general framework. Rather than attempting to reverse misperceptions in people’s minds, Nyhan and Reifler (65) used a mailed reminder of fact-checking services to see if the reminder would deter politicians from making false statements on the campaign trail.
Experimental work generally operationalizes mis/disinformation in one of several ways. First, it is oftentimes a manipulated variable, with the most common manipulations taking the form of providing a false piece of information to experimental participants. These are typically real or constructed news articles or “dispatches” (e.g., refs. 66 and 67) but might also be brief posts or headlines shared on social media (e.g., ref. 68), generic statements or statistics (e.g., refs. 60 and 69), quotes from a politician (e.g., ref. 70), or recordings of news reports (e.g., ref. 71). After exposure, participants will receive some form of retraction notice, thus turning the original information into misinformation.
Misperceptions are typically assessed after exposure to an experimental stimulus through some form of factual knowledge questions, attitudinal items, or inference queries. Factual knowledge questions might take the form of basic fact-recall items based on information in the communication to which the participant was exposed (e.g., “On which day did the accident occur?”; ref. 58). These are similar to the measures employed in survey work, and might take the form of true–false items. Some work assesses fact-recall with response booklets, where participants are asked to provide as many event-related details as possible to provide a complete account of the event (e.g., ref. 58).
Attitudinal items are usually posed around the key components of the shared mis/disinformation. For instance, a study about the false link between vaccines and autism first presented participants with misinformation then corrected that information in one of several ways before measuring attitudes related to the misinformation through a series of agree–disagree items (e.g., “Some vaccines cause autism in healthy children” or “If I have a child, I will vaccinate him or her”; ref. 61).
Inference questions are generally open-ended and allow a respondent to either reference the inaccurate content they were originally given, reference the correction to that information, or avoid the context altogether. In their study of a fictitious minibus accident, Ecker et al. (58) asked participants the following inference question: “Why do you think it was difficult getting both the injured and uninjured passengers out of the minibus?” Having first misinformed participants by noting that the passengers were elderly, and then later correcting that information, a reference to the advanced age of the passengers would be evidence of misinformation.
Finally, unique approaches to studying mis/disinformation require unique approaches to measuring outcomes. The Nyhan and Reifler (65) study that used a reminder of fact-checking to see if it deterred politicians from making false statements measured how dishonest the politicians were in their later statements by turning to PolitiFact ratings and searching LexisNexis for any media articles that challenged a statement by any of the legislators in the study.
Theoretical Underpinnings
The Continued Influence Effect.
The backbone of a significant number of studies of mis/disinformation, particularly many of the experimental approaches built around correcting the effects of misinformation on the public, is the so-called continued influence effect (CIE). The CIE refers to the tendency for information that is initially presented as true, but later revealed to be false, to continue to affect memory and reasoning (59). A relatively small group of researchers have made the most headway in this space, primarily exploring the CIE in news retraction and correction studies (e.g., refs. 6, 58⇓–60, 66, 67, and 71⇓–73).
There are multiple proposed explanations for the CIE. The first concerns “mental event models” (74, 75). People are said to build mental models of events as they unfold. However, in doing so, they are reluctant to dismiss key information, such as the cause of an event, unless a plausible alternative exists to replace the dismissed information. If no plausible alternative is available, people prefer an inconsistent model over an incomplete one, resulting in a continued reliance on the outdated information.
The second explanation for the CIE is focused on retrieval failure in controlled memory processes (6). This process can be relatively simple, such as misattributing a specific piece of information to the wrong source (e.g., recalling the subsequently retracted cause of a fire but thinking that information came from the credible police report), or it might be rather complex, having to do with dual-process theory and the automatic versus strategic retrieval of information from memory (76). While a complete overview of dual-process theory is beyond the scope of this paper, this explanation largely focuses on a breakdown in the encoding and retrieval process in memory due to things like time pressure or cognitive overload (73). In short, how we encode information impacts how quickly and with what accuracy we will retrieve information at a later time.
A third explanation for the CIE concerns processing fluency and familiarity. Oftentimes, in producing a retraction we repeat the initial false information, which may inadvertently increase the strength of that information in the receiver’s memory and their belief in it by making it more familiar (73). When the receiver is later called upon to recall the event, the mis/disinformation is more easily recalled, thereby giving it greater credence. Finally, there is some evidence that the CIE might be based on reactance effects, whereby people do not like being told what to think and push back when they are told to disregard an earlier piece of information by a retraction. This explanation has been largely tested in courtroom settings where jurors are asked to disregard a piece of evidence after being told it is inadmissible (6).
Motivated Reasoning.
Since at least the mid-20th century, scholars have noted that partisans are selective in both their choice and processing of information. The biased processing of content has come to be known as “motivated reasoning.” Motivated reasoning has become a popular concept in mis/disinformation research, particularly for issues with a strong partisan divide (e.g., refs. 13, 61, 66, 72, and 77).
Several mechanisms have been proposed to explain motivated reasoning, including the prior attitude effect, disconfirmation bias, and confirmation bias (78). The prior attitude effect occurs when “people who feel strongly about an issue … evaluate supportive arguments as stronger and more compelling than opposing arguments” (78). Disconfirmation bias argues that “people will spend more time and cognitive resources denigrating and counterarguing attitudinally incongruent than congruent arguments” (78). Individuals are engaging in confirmation bias when they choose to expose themselves to “confirming over disconfirming arguments” when they are given freedom in their information choice (78). Additional work has expanded upon the mechanisms noted here. For instance, Jacobson’s (79) selective perception argues that “people are more likely to get the message right when it is consistent with prior beliefs and more likely to miss it when it is not” (79), while his selective memory suggests that “people are more likely to remember things that are consistent with current attitudes and to forget or misremember things that are inconsistent with them” (79). In the context of mis/disinformation, motivated reasoning can help explain why some people may be resistant to new information that, for example, contradicts a believed link between vaccinations and autism (64).
Other Concepts Common to the Literature.
Factors related to the CIE and motivated reasoning that are also common in the mis/disinformation literature include echo chambers (“polarized groups of like-minded people who keep framing and reinforcing a shared narrative”; ref. 80), filter bubbles (“where online content is controlled by algorithms reflecting user’s prior choices”; ref. 44), worldviews (audience values and orientation toward the world, including their political ideology; ref. 6), and skepticism (the degree to which people question or distrust new information or information sources; ref. 6). These concepts generally help explain the resistance to correcting information that forms the foundation of the CIE.
Trends in the Findings
How Big Is the Problem?
As noted, content analysis work and computational text analyses have helped scholars better understand the scope of the mis/disinformation problem. A complete summary of the studies in this space is not feasible; however, some patterns are worth noting. First, there is often convergence in results even with vastly different approaches to studying the problem. The work on vaccine mis/disinformation represents one area where scholars have generally coalesced in their research findings. For example, Basch et al. (24) explored videos about vaccines on YouTube and found that a strong percentage reported a link between vaccines and autism, a finding that was echoed by Donzelli et al. (25) in their exploration of the same topic and platform. Those findings have been complemented by Moran et al. (19) and Panatto et al. (11), who identified similar false claims about links between vaccination and autism and Gulf War syndrome, respectively, in their samples of web pages. Computational analyses focused on climate change communication have also generally identified problems with mis/disinformation. For example, Boussalis and Coan (38) found increases in climate change mis/disinformation over time, arguing that the “era of science denial” is alive and well, while Farrell (36) found evidence that organizations that produce climate contrarian texts exert strong influence within networks and therefore wield great power in the spread of information.
At the same time, results have not always been consistent, even when exploring the same issue within the same medium. For instance, researchers conducted a search of “Ebola” and “prevention” or “cure” on Twitter, a search that returned a large set of tweets, of which 55% were said to contain medical mis/disinformation with a potential audience of more than 15 million (as compared to about 5.5 million for the medically accurate tweets) (20). Also on Twitter, Jin et al. (21) looked at rumor spread in the immediate aftermath of news of the first case of Ebola in the United States. They found rumors to represent a relatively small fraction of the overall Ebola-related content on the platform. They also found evidence that rumors typically remain more localized and are less believed than legitimate news stories on the topic. All told, the work focused on identifying the scope of the mis/disinformation problem, while oftentimes varying in approach, has consistently found evidence for at least some degree of concern, although pinpointing the exact nature of the problem has proven difficult.
Combatting the Spread of Misinformation.
Computational analyses, including algorithm creation, have allowed for a better understanding of how mis/disinformation spreads, particularly in the online environment. This work is promising for alerting people to likely pieces of false content and has potential for limiting its spread. Vosoughi et al. (41) focused on mis/disinformation identification. They explored the linguistic style of rumors, the characteristics of the people who share them, and network propagation dynamics to develop a model for the automated verification of rumors. They tested their system on 209 rumors across nearly 1 million tweets and found they were able to correctly predict 75% of the rumors, and did so faster than any other public source. Similarly, Ratkiewicz et al. (42) created the “Truthy” system, which identified misleading political memes on Twitter through tweet features like hashtags, links, and mentions.
The work on rumor control has also yielded important findings. Pham et al. (81) developed an algorithm for identifying a set of nodes in a social network that, if removed, will severely limit the spread of mis/disinformation. The authors claim that their approach is not only efficient but a cost-effective tool for combatting mis/disinformation spread. Similar algorithms have been developed by Saxena et al. (82) and Zhang et al. (83). In each case, the authors argue that their algorithmic approach can dramatically disrupt information spread, preventing exposure to a large number of nodes. Of course, the question with these works, and others not outlined here, is how nodes will ultimately be removed from a network, and under what circumstances it is ethically and legally feasible to remove or silence a social media user.
Perhaps because of these questions, Tong et al. (45) focused on stifling the spread of mis/disinformation by identifying it early, seeding key nodes in a social network with accurate information, and allowing those users to spread the accurate information to others before exposure to the false content. Their approach was found effective for rumor blocking, suggesting there are multiple promising avenues for identifying and controlling the spread of mis/disinformation online.
Combatting Misinformation within Members of the Public.
Arguably the most extensive work aimed at combatting misinformation is the experimental work on retractions and corrections, usually in the context of the CIE. Once again, this work has generally focused on honest mistakes in reporting rather than more deliberate attempts to deceive, which is likely to impact how receptive audiences are to correcting information. Work in this space has focused on altering the impact of a retraction by being more clear and direct with its wording (74), repeating it multiple times (84), altering the timeline for the presentation of the retraction (74, 85), and providing supplemental information alongside it (i.e., giving reasons why the misinformation was first assumed to be factual; ref. 86). Other work has focused on the emotionality of the misinformation (87) or has manipulated how carefully a respondent is asked to attend to the presented information (88).
Virtually no work has been successful at completely eliminating the effects of misinformation; however, some studies have shown promise for reducing misperceptions. Among the most promising involves delivering warnings at the time of initial exposure to the misinformation (6). Ecker et al. (58) found that a highly specific warning (a detailed description of the CIE) reduced but failed to fully eliminate the CIE. A more general warning having to do with the limitations of fact checking in media did very little to reduce reliance on misinformation. Cook et al. (56), as well as van der Linden et al. (57), have found promising evidence that audiences can be inoculated against the effects of false content by providing very specific warnings about issues like false-balance reporting and the use of “fake experts.” It is worth noting that warnings are most effective when they are administered prior to mis/disinformation exposure (89).
The repetition or strengthening of retractions has been found to reduce, but again not eliminate, the CIE (6). The best evidence of this is from a study by Ecker et al. (73), who varied both the strength of the misinformation (one or three repetitions) and the strength of the retractions (zero, one, or three repetitions). Their experiments revealed that after three presentations of misinformation a single retraction served to lessen reliance on misinformation, with three retractions reducing it even further. However, the repetition of misinformation also had a stronger effect on thinking than the repetition of the retraction (73). Therefore, efforts to correct a misperception through repetition of a retraction might actually result in boomerang effects as retractions oftentimes involve repeating the original misinformation (90). Further, there is at least some evidence that the repetition of a retraction produces a “protest-too-much” effect, causing message recipients to lose confidence in the retraction (86).
The provision of alternative narratives has also shown promise for reducing the CIE. An alternative narrative fills the gap in a recipient’s mind when a key piece of evidence is retracted (e.g., “It wasn’t the oil and gas [that caused the fire], but what else could it be?”; ref. 6). There is some fMRI data that corroborates this theory as it found that the continued influence of retracted information may be due to a breakdown of narrative-level integration and coherence-building mechanisms implemented by the brain (71). To maximize effectiveness, the alternative narrative should be plausible, should account for the information that was removed by the retraction, and should explain why the misinformation was believed to be correct (6).
Other factors that have been tested include recency and primacy effects, with recency emerging as a more important contributor to the persistence of misinformation as people generally rely more on recent information in their evaluations of retractions (59). Familiarity and levels of explanatory detail have also been tested (60). The authors found that providing greater levels of detail when correcting a myth produced a more sustained change in belief. They also found that the affirmation of facts worked better than the retraction of myths over the short term (1 wk), but not over a longer term (3 wk), and that this effect was most pronounced among older rather than younger adults. It is also worth noting that combining approaches can enhance their effects. For example, merging a specific warning with a plausible alternative explanation can further reduce the CIE compared with administering either of those approaches separately (58).
Source work has also been popular for combatting the effects of false information. For instance, having the refutation of a rumor come from an unlikely source, such as someone for whom the refutation runs counter to their personal or political interests, can increase the willingness of even partisan individuals to reject the rumor (66). It is worth noting, however, that the author conducted a content analysis of rumor refutation by unlikely sources in the context of healthcare reform and found it to be an exceedingly rare event.
Driven by its role in the proliferation of mis/disinformation, Bode and Vraga (61) have focused their correction studies on social media. One study did so using the “related stories” function on Facebook. This work presented participants a Facebook post that contained inaccurate content and then manipulated the related stories around it to either 1) confirm, 2) correct, or 3) both confirm and correct that information. The analysis revealed a significant reduction in misperceptions among those participants who received content designed to correct it. They later looked at source credibility in the context of information shared on Twitter and found that while a single correction from another social media user failed to significantly reduce misperceptions, a single correction from the CDC could impact misperceptions (62). In fact, corrections from the CDC worked best among those with the highest levels of initial misperception. They further investigated whether providing a source was necessary to curb misperceptions by having two individual commenters discredit the information in a Facebook and Twitter conversation (68). In one condition those users provided a link to debunking news stories from the CDC or Snopes.com, while in the other they did so without reference to any outside sources. Their results suggest a source is needed to correct misperceptions.
Finally, outside of factors related to the misinformation itself or the retraction, individual-level differences have also been tested in the context of the CIE and misinformation correction studies, including racial prejudice (72), worldview and partisanship (70, 91), and skepticism (92), with mixed results scattered across studies.
Gaps in the Literature and Moving Forward
While misinformation remains a relatively new topic of public concern, scholars have been addressing issues in this space for quite some time. The result is a large body of literature, but one with significant gaps. Perhaps most worrisome is that much of the work has focused on combatting misinformation, and, importantly, not disinformation. This distinction is subtle, but important. The bulk of the studies focused on the CIE, for instance, have focused on small journalistic errors in reporting (e.g., misrepresenting the cause of a fire) and have largely avoided issues characterized by more deliberate attempts to deceive and persuade. Of course, the major controversy surrounding false information has less to do with honest errors in writing and much more to do with deliberate attempts to deceive. The early retraction studies (e.g., refs. 58 and 87) have provided a strong foundation of initial findings, but we must push these further with highly partisan issues and audiences.
Related to the point above, relatively few studies have explored methods for inoculating individuals from mis/disinformation. As noted, progress has been made in this space with regard to issuing warnings about things like the CIE prior to misinformation exposure (58). Other work has explored factors like false-balance reporting and the use of “fake experts,” also with promising results (56, 57). While such work does not always completely prevent mis/disinformation from taking hold, it does present a promising avenue for better understanding the causes of mis/disinformation and ways to prevent its spread.
A third gap in the literature, one articulated by Lewandowsky et al. (6), has to do with the relative dearth of studies focused on individual-level differences that exacerbate or attenuate things like the CIE. The authors specifically reference intelligence, memory capacity and updating abilities, and tolerance for ambiguity as factors worthy of research attention. However, other factors, including elaborative processing, social monitoring, and a host of variables related to media use and literacy, also remain untested. Greater attention should also be paid to the role of emotion in both the processing of mis/disinformation and its spread (6).
A fourth gap in the literature has to do with better understanding the mechanisms that explain the persistence of mis/disinformation in our minds. Different pathways have been suggested for explaining why mis/disinformation is so difficult to combat. However, relatively few studies have attempted to test competing theories, instead choosing to speculate on explanations post hoc. The functional MRI work of Gordon et al. (71) is both an interesting approach and promising step in furthering our understanding of information persistence. Without more definitive attempts to explain the process through which mis/disinformation seemingly infects our brains, we are doomed to continue the uphill battle against this content.
A common thread in much of the literature cited in this paper is a focus on individuals—typically everyday citizens—and their perceptions. Of course, mis/disinformation can also influence other populations, including political elites, the media, and funding organizations. Indeed, it is arguably most impactful when these audiences are reached as they represent potentially powerful pathways to political influence. Unfortunately, there is a relative dearth of work in this space, at least as compared to studies focused on individual perceptions. Notable exceptions can be found in some of the computational work focused on climate change countermovements (e.g., refs. 36 and 38⇓–40). For example, Brulle (93) recently examined the network of political coalitions, including those in coal and oil and gas sectors, to better understand the organization and structure of a movement opposed to mandatory limits on carbon emissions. Further work focused on the nature and makeup of networks involved in the spread of false content is an especially fruitful path for future research.
Finally, it is worth noting that addressing any of the above gaps in the literature will be very difficult without paying greater attention to issues of conceptualization and operationalization that plague many of the key concepts in the space. Far too many studies have defined or measured misinformation in ways that are actually reflective of different concepts, including disinformation, ignorance, or misunderstandings. A necessary first step in improving our understanding of mis/disinformation impacts and combatting their negative effects, therefore, is to clearly and appropriately define what we mean by key terms and how we should be measuring them in empirical studies of the topic."
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I am looking for empirical studies that examine the use of non-traditional grading in higher education. This means NOT using A-F grades during a course (even if, at the conclusion of the course, the university requires the instructor to assign a grade using the traditional A-F scale). This could include any of the following: narrative grading (grading with the use of written narratives), portfolio assessment, self-assessment, student-teacher collaborative assessment, formative assessment, etc.
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This is how they work in elementary school. At the university, the student must understand his real level and the teacher's assessments largely describe this. As for the "self-assessment, student-teacher collaborative assessment" - it's generally ridiculous. In order to evaluate, student needs to know at least something. They can also vote in an academic group - it will be very democratic.
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I plan in conducting narrative inquiry on students' self-efficacy (SE) and self-regulated writing strategy (SRWS). I will involve students categorized as 4 high achievers in class. My procedures are administering 2 questionnaires as scales of SE and SRWS, finding relationship between SE and SRWS, narrative interview. Am I allowed to do these scientifically?
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From my storytelling-perspective the question is whether you gear at labelling overlapping themes within the results of doing justice to differences within and between answers. Since your appreciation of Morgan's reaction I presume the labelling - so take Morgan's advice
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Hello everyone, the topic of my thesis is pre-Islamic poetry between Orientalism and the narration, and I would like to compare the Orientalists’ methods of research in parallel with the method of the narrative among the Arabs.
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Since you intend to focus on pre-Islamic poetry, comparing the Orientalists’ methods of research, I would suggest Orientalism, Said's "foundational document in the field of postcolonialism , providing a framework and method of analysis to answer the how? and the why? of the cultural representations of Orientals"!
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I've recently written and submitted a literature review that provides a narrative synthesis of 30 studies, half of which are quantitative (using various methods) and half qualitative. I make clear in the introduction that part of the value of the review is in bringing together a wide range of studies that look at the same issue from a range of disciplinary perspectives, using a variety of methods.
On review, one of the reviewers has suggested that I combine the findings in a meta-analysis. Is this even feasible given that the review covers both quantitative and qualitative papers? If so, what methodology would I use? (I'm aware of the Timulak papers on qualitative meta-analysis, but am not aware of anything that enables you to combine quan and qual). The methods of the included studies range from discrete choice analyses to quantitative content analyses, to semi-structured interviews, to ethnography. Surely much of the value of each study would be lost if they were somehow pulled together in a meta-analysis?
Would I be justified in rejecting this suggestion and reiterating that the review provides a narrative synthesis of a range of study types?
Thanks.
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Hello
In my opinion, you have to review MIXED METHODOLOGY:
Best regards
Ph.D. Ingrid del Valle Garcia Carreño
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The strengths of a systematic review include a high level of evidence, avoidance of bias, a thorough search, and in addition these are probably more easily accepted for publication. Narrative reviews can address broad topics, and appear more flexible to conduct. If a meta-analysis is not planned, how would one choose between a narrative and systematic review format?
My guess is that for a relatively unexplored topic, or subject with little research, it wouldn’t make as much sense to use the systematic format considering little results will be found and/or synthesized. I have learned from and referenced narrative reviews that were conducted relatively rigorously. However, it seems that the trend is to conduct systematic reviews whenever possible. What do you think?
For further reading:
Franco, Juan Víctor Ariel, et al. "Syntheses of biomedical information: narrative reviews, systematic reviews and emerging formats." Medwave 18.07 (2018).
Rother, Edna Terezinha. "Systematic literature review X narrative review." (2007): v-vi.
Greenhalgh, Trisha, Sally Thorne, and Kirsti Malterud. "Time to challenge the spurious hierarchy of systematic over narrative reviews?." European journal of clinical investigation 48.6 (2018).
Thorne, Sally. "Rediscovering the “Narrative” review." (2018): e12257.
Pae, Chi-Un. "Why systematic review rather than narrative review?." Psychiatry investigation 12.3 (2015): 417.
Thanks,
Rob
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Dear @Robert Trager you already mentioned narrative review is flexible. In addition, unlike systematic review, narrative review can be done by a single author. In my view, if you have resources and collaborators go for systematic review.
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I want to write a theory development piece and I am proposing a process model. As Cornelissen (2017) editorial suggests, you can adopt a narrative style for writing a process paper. My question is can I use statements similar to propositions with the title of "narrative"?
For example, my proposition is: "In the pre-adoption stage, users have an initial attitude toward the technology that affects their decision in the next stage (phase)..."
- Cornelissen, J. (2017). Editor’s comments: Developing propositions, a process model, or a typology? Addressing the challenges of writing theory without a boilerplate.
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Thank you Justin Nicholes Justin Nicholes , I already got an answer from Suzzane Rivard, former senior editor at MISQ theory and review. She was open to the idea of "narratives", and i used a combination of propositions and narratives (which is different from narrative style of the prose) to reflect all aspects of the theoretical contributions that I wish to present.
And interestingly I don't have any idea of your classification of theory purposes (tell a story, argue for position, combination). If you please share the article for this taxonomy/ typology I would be thankful.
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Whenever researchers start with evidence-based reviews, whether they are scoping, rapid reviews, systematic reviews, or even current form of narrative reviews, they face problems at every steps which require assistance from people who have already been doing these kind of reviews. These problems can range from topic selection, to team formation to database search to registration and many more. Here I would like to initiate a discussion to identify the problems
faced by each and every researcher who is either planning to start or is currently doing reviews and welcome views to look for solutions for these problems with a collective approach.
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One of the most common problems encountered is the lack of randomized controlled clinical trials and the heterogeneity of the statistical analysis. These create an issue when performing meta analysis on the included studies. Please find the systematic review reference below from our group.
Gandhi V, Mehta S, Gauthier M, et al. Comparison of external apical root resorption with clear aligners and pre-adjusted edgewise appliances in non-extraction cases: a systematic review and meta-analysis. Eur J Orthod. 2021;43(1):15-24. doi:10.1093/ejo/cjaa013
Abu Arqub S, Mehta S, Iverson MG, Yadav S, Upadhyay M, Almuzian M. Does Mini Screw Assisted Rapid Palatal Expansion (MARPE) have an influence on airway and breathing in middle-aged children and adolescents? A systematic review. Int Orthod. 2021;19(1):37-50. doi:10.1016/j.ortho.2021.01.004
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Considerable discussion within the historical fraternal about history, revisionism and statues. The grand narratives of the past often seem too simplistic for what are often very complex issues which are being written about. The concerns about statues are often couched on statements about rewriting history or redefining the narratives (though often statues are erected long after the individual/event they depict)
Now more than ever there needs to be a reflection about historical narratives. Whose history is being told? Which narratives of the past are being ignored or suppressed? Is it right for historians to bring to their discipline ‘value judgement’ about the past or is their task purely to describe and analyse it? These are important issues, certainly in the west, and wondered what others think about these issues. Maybe once again we need to address the question ‘what is history’ (building upon the earlier works of historians such as E H Carr) and modern attitudes
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Dear. Dr. Stuart B. Jennings,
History is a continuous dialogue between the Past and the Present, it is also a "continuous interaction" between the "Historian of the historical turn" and the events that occurred, these being narrated by the "winners", not by the "defeated". Today, in the telematic world in which we move, we need to “reprogram ourselves” and re-investigate the events narrated in the Past, both by “winners” and by “losers”, to arrive at a “more correct” interpretation. of History. Only in this way can we more accurately record the events of the past. The most famous case, due to its historical importance, is that of Christopher Columbus [1451-1506] whose History has yet to be written. See in this regard my research papers to reflect on "why" of the current demolition of their statues in different parts of our world.
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Would you please clear me how I can do the narrative analysis based on the transcripts of in-depth interviews?
I actually collected the narratives of participants, can I now conduct thematic analysis? if so, what is the name of such analysis?
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I believe that nowadays, interacting between narrative analysis and thematic analysis implies knowing how to fit perfectly with the experience and the meaning of life experienced as a special and motivated fact in our case on a literary level. It is about interacting in the first person, where "Time" plays its important role, not only because of the importance we give to "information", but also because of the approach that is already being given to the "New Social Phenomenon" that we are living.
Both analyzes interact, Dear.Dr .Tauhid Hossain Khan, they are not divided.
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The narrative of memory dialogues with the 'time of the 'experience recorded' and the 'time of the narrative of remembrance'. Paul Ricoeur in "Time and Narrative" indicates the paradoxalities of the hermeneutic circle between the act of narrating the fact (remembered) and temporal dynamics. What can be understood about the plasticity of time in the dialogues of memory? Something that Ricoeur himself will later explore in "Memory, History and Forgetting". But would this temporal plasticity be a relevant factor in the transformation of non-biographical memory into biographical memory?
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Thank you very much, Rooney Pinto, for the clarification. Now I see the difference between one thing and another. I tell my PhD student (he has been researching intergenerational memory transmission for two years, and the fieldwork is over) to contact you through Researchgate. Of course, if this doesn't bother you. Kind regards, Maribel
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More and more clinicians have interesting experiences with glucose 5% injections. However, we lack fundamental research to support our clinical findings. (below: more information about Glucopuncture / glucose 5% injections)
Jan Kersschot
Glucopuncture: Introduction
1. Definition
Glucopuncture is a nonsteroidal injection therapy for the management of a variety of nonrheumatic musculoskeletal conditions. It consists of series of sessions of multiple regional glucose 5% injections into the dermis and into muscles, tendons, and ligaments. Intradermal injections are given to modulate referred pain and intralesional injections are applied to support tissue repair.
2. History
Glucose and dextrose injections have been used for several decades in prolotherapy ([i], [ii], [iii], [iv], [v], [vi], [vii], [viii], [ix]). Hypertonic dextrose prolotherapy typically uses high concentrations of dextrose (10% net concentration or more). Such hyperosmolar solutions lead to localized cell destruction. This phenomenon creates a local inflammatory reaction. This may lead to tissue proliferation – hence the description prolotherapy - and even formation of scar tissue.
Over the last decade, low concentrations of glucose 5% (or dextrose 5%) have become more popular ([x], [xi], [xii], [xiii], [xiv], [xv], [xvi], [xvii]). Clinical experience indicates that glucose 5% injections may be effective for the management of a variety of musculoskeletal conditions. Despite interesting clinical outcome, glucose 5% injections have not received much attention among family physicians, sports doctors, or orthopaedic surgeons. The term Glucopuncture (GP) was introduced in January 2021 to change that situation ([xviii]).
3. Mechanism of Action
3. 1. Pain Modulation and Tissue Repair
Most hypotheses about glucose injections are focused on pain modulation (e.g., vanilloid receptors, neural inflammation, gate control). But these theories on pain modulation are not specific for glucose injections. Furthermore, these theories do not explain the beneficial effects of Glucopuncture on tissue repair. Certain tissues seem to function better after a few sessions. Apparently, local glucose injections support cellular function and consequently lead to tissue repair clinical functional improvement. This functional improvement leads to, for example, less stiffness when injecting into muscle, and more joint stability when injecting into collateral bands or ligaments. To explain this functional component, a new hypothesis has been proposed, the ATP hypothesis.
3.2. The ATP Hypothesis
Glucose is the major energy source for cellular health. One glucose molecule gives rise to more than 30 ATP molecules during the aerobic respiration. The conversion of ATP into ADP releases about 30 kJ/mol energy to the cells. In other words, glucose can be considered as a direct provider of energy (one molecule delivers more than 900 kJ/mol) to cell metabolism.
When tissues are damaged because of trauma, overuse or other causes, the cells need to regenerate as quickly as possible. This physiological tissue regeneration requires an additional amount of energy in the cells. In normal circumstances, energy supply is abundant to meet the higher demand. The cells are so to speak self-sufficient when it comes to ATP production. But when the need for ATP is elevated, there may be a temporary lack of ATP and as a result physiological recovery of that tissue may become impossible. The latter may lead to poor tissue healing. Providing extra glucose to the cells during these moments of repair might lead to extra ATP production. In this sense, it is hypothesized that Glucopuncture improves tissue repair of, for example, muscles, tendons, and ligaments.
3.3. The Effect of Glucose on Tiny Nerve Branches
Especially peripheral nerve endings seem to respond well to adjacent glucose injections. This effect is not observed when glucose is injected intravenously, which may mean that the mechanism of action is located in the extracellular matrix at the injection site. More research is required to further explore this. One can approach the peripheral nerves directly, for example, when injecting close to the median nerve (carpal tunnel) or greater occipital nerve. But clinical experience has illustrated that it is not always necessary to inject adjacent to peripheral nerves. Reaching the finer branches with glucose seems to be equally important. These extremely tiny nerve endings are present in muscles, tendons, ligaments, and so on. These fine nerve branches are also impossible to find during clinical examination – let alone inject each one of them separately. That is why multiple injections are given in the entire region.
3.4. The Effect of Glucose on Dermal Sensory Nociceptors
Sensory receptors are found everywhere in the body. They are also abundant in dermis. That is probably the reason why superficial injections of glucose can be more influential than expected. It is sometimes said that the skin is the largest sensory organ of the human body. These dermal sensory receptors are an important part of the somatosensory system. These receptors include mechanoreceptors, nociceptors, and thermoreceptors. Especially dermal nociceptors are important to explain the pain modulating effects of Glucopuncture while injecting glucose intradermally.
In other words, it is hypothesized that peripheral nerves which are irritated or inflamed, require more glucose than normally because they are mechanically irritated, inflamed or both. At some point, the ATP levels are too low and ‘batteries’ are empty. Providing additional ATP through glucose injection might resolve this issue temporary. This so-called ‘charging’ of the cells must be repeated on a regular basis until the cells can continue to function without external sources of ATP. That might explain why it is crucial to repeat the Glucopuncture sessions on a regular basis, especially in the beginning of treatment. This theory is still hypothetical and more research in this field is required to confirm these statements.
3.5. Glucose transport across the cell membrane
Glucose is transported across the cell membrane ([xix]) by a specific saturable transport system, which includes two types of glucose transporters: 1) sodium dependent glucose transporters (SGLTs) which transport glucose against its concentration gradient and 2) sodium independent glucose transporters (GLUTs), which transport glucose by facilitative diffusion in its concentration gradient.
The understanding of glucose transport after extracellular injection and its consequent effect on small branches of peripheral nerve endings in, for example, muscle tissue, tendons, ligaments, and its effect on dermal nociceptors is obviously still incomplete and needs further investigation. It is hoped that the introduction of Glucopuncture and its promising clinical effects might stimulate more research in the field of neural inflammation and the beneficial effects of regional glucose injections. Unfortunately, glucose is an inexpensive product which cannot be patented, so it is very unlikely to receive funding for large randomized clinical trials from pharmaceutical companies.
[i] Reeves KD, Sit RW, Rabago DP. Dextrose Prolotherapy: A Narrative Review of Basic Science, Clinical Research, and Best Treatment Recommendations. Phys Med Rehabil Clin N Am. 2016 Nov;27(4):783-823. doi: 10.1016/j.pmr.2016.06.001. PMID: 27788902
[ii] Distel LM, Best TM. Prolotherapy: a clinical review of its role in treating chronic musculoskeletal pain. PM R. 2011 Jun;3(6 Suppl 1):S78-81. doi: 10.1016/j.pmrj.2011.04.003. PMID: 21703585.
[iii] Ganji R. Dextrose prolotherapy for improvement of rotator cuff lesions: ready for clinical use?. Hong Kong Med J. 2018;24(4):429–430. doi:10.12809/hkmj187480
[iv] Rabago D, Nourani B. Prolotherapy for Osteoarthritis and Tendinopathy: a Descriptive Review. Curr Rheumatol Rep. 2017 Jun;19(6):34. doi: 10.1007/s11926-017-0659-3. PMID: 28484944.
[v] Rabago D, Kansariwala I, Marshall D, Nourani B, Stiffler-Joachim M, Heiderscheit B. Dextrose Prolotherapy for Symptomatic Knee Osteoarthritis: Feasibility, Acceptability, and Patient-Oriented Outcomes in a Pilot-Level Quality Improvement Project. J Altern Complement Med. 2019;25(4):406–412. doi:10.1089/acm.2018.0361
[vi] Reeves KD, Hassanein KM. Long-term effects of dextrose prolotherapy for anterior cruciate ligament laxity. Altern Ther Health Med. 2003 May-Jun;9(3):58-62. PMID: 12776476.
[vii] Dwivedi S, Sobel AD, DaSilva MF, Akelman E. Utility of Prolotherapy for Upper Extremity Pathology. J Hand Surg Am. 2019 Mar;44(3):236-239. doi: 10.1016/j.jhsa.2018.05.021. Epub 2018 Jun 23. PMID: 29945842.
[viii] Reeves KD, Hassanein K. Randomized prospective double-blind placebo-controlled study of dextrose prolotherapy for knee osteoarthritis with or without ACL laxity. Altern Ther Health Med. 2000 Mar;6(2):68-74, 77-80. PMID: 10710805
[ix] Seven MM, Ersen O, Akpancar S, Ozkan H, Turkkan S, Yıldız Y, Koca K. Effectiveness of prolotherapy in the treatment of chronic rotator cuff lesions. Orthop Traumatol Surg Res. 2017 May;103(3):427-433. doi: 10.1016/j.otsr.2017.01.003. Epub 2017 Feb 16. PMID: 28215611.
[x] Maniquis-Smigel L, Reeves KD, Rosen JH, et al. . Short term analgesic effects of 5% dextrose epidural injection for chronic low back pain. A randomized controlled trial. Anesth Pain Med 2017;7:e42550.
[xi] Köroğlu, Özlem & Orscelik, Aydan & Karasimav, Özlem & Demir, Yasin & Solmaz, İlker. (2019). Is 5% dextrose prolotherapy effective for radicular low back pain? Gulhane Medical Journal . 2019, Vol. 61 Issue 3, p123-127. 5p.
[xii] Lyftogt, John. (2007). Subcutaneous prolotherapy treatment of refractory knee, shoulder, and lateral elbow pain. Australasian Musculoskel Med. 12. 107-109.
[xiii] Weglein, AD. Neural Prolotherapy. Journal of Prolotherapy. 2001;3(2):639-643
[xiv] Paprottka KJ, Lehner A, Fendler WP, et al. Reduced periprocedural analgesia after replacement of water for injection with glucose 5% solution as the infusion medium for 90Y-Resin microspheres. J Nucl Med. 2016;57(11)(1679-1684).
[xv] Mansız-Kaplan B, Nacır B, Pervane-Vural S, Genç H. Pain relief in a patient with snapping scapula after 5% dextrose injection. Turk J Phys Med Rehabil. 2020 Aug 18;66(3):368-369. doi: 10.5606/tftrd.2020.4169. PMID: 33089095; PMCID: PMC7557628.
[xvi] Solmaz İ, Akpancar S, Örsçelik A, Yener-Karasimav Ö, Gül D. Dextrose injections for failed back surgery syndrome: a consecutive case series. Eur Spine J. 2019 Jul;28(7):1610-1617. doi: 10.1007/s00586-019-06011-3. Epub 2019 May 21. PMID: 31115685
[xvii] Amanollahi, A., Asheghan, M., & Hashemi, S. E. (2020). Subacromial corticosteroid injection versus subcutaneous 5% dextrose in patients with chronic rotator cuff tendinopathy: A short-term randomized clinical trial, Interventional Medicine and Applied Science IMAS, 11(3), 154-160
[xviii] Kersschot J, Glucopuncture: Series of Regional Multiple Glucose 5% Injections. Adv Complement Alt Med. 6(2). ACAM.000636.2021.
[xix] Jurcovicova J. Glucose transport in brain - effect of inflammation. Endocr Regul. 2014 Jan;48(1):35-48. doi: 10.4149/endo_2014_01_35. PMID: 24524374.
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Jan Kersschot Excellent topic! Prolotherapy is the near-future. You should better refer to Spine Intervention Society as their associated clinicians/researchers can help you provide with the data for your hypothesis testing.
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Forgive me if this seems like a silly question, but if I am publishing a narrative review, and not collecting any data of my own, do I need IRB approval?
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no - there was no direct use of human subjects and if it is a narrative then the studies referenced showed already be in the public domain
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Halton (Chip) Arp along with Edwin Hubble were the greatest astronomer/astrophysicists of 20th century. While Hubble's name is much used and abused; Arp's (some call him the Galileo of modern times) name is hardly ever mentioned in the narrative of official astrophysics and cosmology. Arp's name is famously associated with the Quasars, but in the present narrative on Quasars in Wikipedia, his name does not even merit any mention!
Quasars represent the biggest embarrassment of the Big Bang creation cosmology, based on mathematical idealism and the General Relativity (RG) that has replaced theology as the ruling idea for monopoly capitalism. Since it was first suggested by Halton (Chip) Arp few decades ago that high red shift quasars are ejects from nearby (low red shift) active galaxies, mountain of rapidly accumulating observational evidence including quasar – galaxy associations, close pair of quasars, their alignments and groupings, red shift periodicity and quantized redshifts effect etc. [1 - 4 ] is making breeches in the high walls of closely guarded Big Bang paradigm that obstinately refuges to accept [5] the ejection theory. In one of the most famous cases involving NGC 4319 and the quasar Markarian 205 Arp and his associate Jack Sulentic demonstrated a luminous link between the two; both from the pictures of an amateur astronomer and the one taken later by Hubble Space Telescope as shown below (Fig. 1):
📷📷
Fig. 1
But it was as usual strongly denied [6], as a line-of-sight occurrence. Statement by Arp [7]: “Science, 11 Oct. 2002, p. 345, ran a small article on the statements from both sides, but most science magazines just accepted the NASA release as refutation of the connection. Personally, I can say that after more than 30 years of evidence disputed by widely publicized opinions that the bridge was false, I was saddened that not one prominent professional has now come forward to attest that it is, in fact, real”.
Arp was forgotten by mainstream astrophysics community and ejection trails of the quasars were totally abolished and vehemently denied, even after the following "Deep Spectroscopy in the Field of 3C 212" image turned up [8]. The quasar 3C 212 photo is shown (Fig. 2), overlaid with a green-tinted radio emission map. To the SE there is an optical feature nearly matched by a radio feature, but in the NW there is a brilliant horse-head-shaped radio emission which connects unbroken to the QSO with a long neck in between. Beyond this emission, further out from the QSO but in a perfect line with the QSO -radio horsehead axis, there is an optical horse's head, identical in every significant morphological way (i.e. they look just the same). Both radio & optical horseheads are revealed in the article to be close doublets, with one emission at the eye and another of the mouth of the horseheads.
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Fig. 2
In line with official cosmology, the original authors [8] interpreted this image as, “.. the horsehead features ... ...are ... not ...related”. Now Bruno Leibundgut and Jesper Sollerman [9] have a good laugh and interpret the image in the following way, in line with poor Halton (Chip) Arp, long after he is gone and forgotten!
“Some reflection shows us what is happening in this photo. The QSO 3C212 is surrounded by a spherical shell of material similar to rings seen around stars (which are spherical shells seen edge-on). It has ejected the doublet f & g along its polar axis. The horsehead f represents a significant amount of material, and left a radio trace of its emergence out of 3C212. When f and g reached the spherical shell they splashed through, leaving a radio signature on the shell. The horsehead f left a horsehead-shaped splash. The simple object g splashed through and has left simple ripples in the shell. Go on, look -- there are two ripples, indicating the spherical shell has two layers. Simple, really, once you see it.
So now it becomes clearer. The QSO 3C212 is at redshift z=1.049, f is at z=0.928, and so is hurtling toward us with radial speed of about z=0.121 (ignoring "instrinsic" redshift component, see below). The redshift of g has been measured at 1.054, so has a small radial speed away from us of z=0.005. There, now that wasn't so hard, was it? All we need to do it accept that redshift can stem from more than just cosmological distance”.
Note: Please see the attached file for the Figs. and References and also the following link:
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Only for the primitive guy it is important who "THE GREATEST" is... to me, every honest soul who devotes his life for his work is respectable...
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The memories of the events, biographical or not, are reconstructed in the memory narratives. In this way, the recollection, or at least, the recollection narrative is influenced by the context (past and present). But, how does the context influence the registration of the biographical event and the narrative of remembrance? How can Context Theory help us to understand the influence of time on narratives?
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Hope this helps... Its a good paper by Parker et al. 2007.
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I am looking for texts on Reference(ing) and/or Referential Processes in Discourse, construction of referents. Works that explore these topics in oral narratives (fiction or real). Thanks.
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Please check some of the works done by Prof. Ganesh Devy
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“It is frequently stated that if more women were in charge of foreign policy, the world would be a more peaceful place. However, despite the fact that women have played important roles, little research has been conducted on the actual foundations of this claim. While female leadership is gaining traction, women in International Relations-related jobs, whether in academia, diplomacy, international organizations, government, or international business, face greater challenges in climbing the seniority ladder than women in other fields, also despite evidence of women’s role in the diplomatic and international arena, the core historical narrative of international politics remained depleted of women....
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Although many analysts will say that remarkable progress has been made in emancipation and the inclusion of women in all spheres of society (international politics, academia) is sufficient to look at the reality that says quite the opposite: there is much left geographical areas where the woman is in a subordinate position, endangered, and even exposed to completely inhumane treatment. The problem is that no society nurtures traditional and patriarchal values ​​that diminish the woman's equal position, so the woman remains forever trapped in the family, private sphere, designated for household chores and child care. A woman is seen as a "service provider" of husband and children and as the primary caregiver. A logical question arises: who can and by what means to help a woman turn the situation in society to her advantage? As part of this complex problem, we can consider the activities of individuals, non - governmental sector, actions of neo-feminist movements, civic activities and initiatives, and state strategies and laws. The focus is on: creating space for the application of respect for human women 's rights and the emancipation of women in society.
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When we are doing a narrative synthesis in the absence of poolable data, which would be the best way to assess the quality/certainty of evidence? I have already used the ROBINS-I tool for the risk of bias but what may be used instead of GRADE after the synthesis?
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Thanks for your valuable question
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My master's thesis topic is on the benefits of oral interactions after shared reading sessions for the development of both language skills and the understanding of narratives, which contributes to better reading skills in the short and in the long term. My view is that it might be too demanding to expect from four and five-year-olds to be able to remember the key elements of a story, concentrate on the teacher's questions/feedbacks and make well-structured sentences all at the same time. It might be more efficient to dedicate specific sessions to teach language, and if books can be used to do so, then they shouldn't be chosen among children literature which is often far too complex for that. I would highly appreciate to know the opinions of people who are more expert than I am on this topic.
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Valuable information and discussion
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My current study explores the psychology of how children learn about other nations through the media and is examining a television series with anthropomorphised animals.
The first stage involved examining the series to better understand how national identities are assigned to animal characters.
I was editing my findings section and happened to notice that the values in columns labelled CFAs and CSAs were equal or close to half the values in IFAs and ISAs, except for the bottom left two cells (28 and 8).
For contexts, the column labels stand for Individual Feature Animals, Collective Feature Animals, Individual Supporting Animals and Collective Supporting Animals.
Feature refers to animals who were the focus of a narrative.
Supporting refers to animals who contributed to a narrative but weren't the focus.
Individual refers to single animals.
Collective refers to groups of two or more animals - like a pod of whales - or references to entire species.
I feel like I might be digging a bit too deep here, but is there a statistical analysis that could potentially identify a relationship between the values presented?
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Thanks for your response.
Based on your suggestion, I ran a chi-square and got x2 (6, N = 317) = 28.78, p < .0001, critical value 12.59.
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I´m doing a systematic review for my final grade project and found out that two of my studies present with high risk-of-bias. Since I only have 5 studies in my review and I will not conduct a meta-analysis on the data, I´m wondering if I can use the data from the two biased studies as part of the narrative data synthesis.
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I believe it is fine to include such studies in your systematic review. However, you should be very transparent in describing the biases and be very cautious when making conclusion out of these studies. Even if you choose to exclude these studies you should be able to explain and justify the reason for not including the studies.
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Narrative is an important subject for the contemporary investigative, educational and creative processes. Its significance derives from the fact that discourse tends to codification, specialization and institutionalization, whereas narrative operates at the margins of discourse, benefiting from diverse, flexible, interdisciplinary knowledge spaces, making discourse problematic and opening it up to the dialogic.
Narrative is a way of thinking and a reading-writing research procedure that reinforces memorization of the past and articulates the present; that addresses itself to a diverse
culture, its know-how, practices and territories; that reconfigures the communicative ecosystem. Narratives are tales that may be written, visual, audiovisual, sounding, performative, and are approached in a panoramic, expanded, hybrid or interactive way, displaying their content through multiple writings and communication platforms where the narrated actors and the spectators taken on participative roles.
As Editor-in-Chief of ACTIO Journal of Technology in Design, Film Arts and Visual Communication, we invite you to submit an article related to narratives. For more information, see the attached document. Thanks for sharing!
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The link by Sotiris Folinas may be of help
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Since 2016 coup attempt CHP has accepted the official narrative of AKP government and its discourse (of rhetoric). I am investigating the reasons of this compliance.
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Perhaps Koray Caliskan can help you. He is on Research Gate.
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This example attached below was made between 11000 and 12000 BCE in present day Colombia and is a greater achievement than European efforts found so far. It is 8 miles long.
So can this qualify as the written word, a narrative and a book?
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I am amazed how you made the leap from painting of animals and diets to a system of writing!!!
“It might demonstrate an earlier birth to writing, but not in Middle East as previously considered. It also shows how sohisticated mesolithic seem actually to have been.”
After reading the article in the website you referenced, I could find nothing about writing.
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I am working right now on a narrative review , What data base can i register this review ?
N.B. PROSPERO only register systematic, ours is narrative
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Ahmad Sabbahi Thanks for your reply
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Is it possible to study the truth box within the narrative level in fiction?
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Good question
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I'm having a large dataset consisting of videos, pictures, narratives and interviews about dairy farming practices. This was informed by practice theory. But how does it inform rigorous analysis of data? Or does it require going back to established procedures coming fro m anthropology, sociology, et cetera?
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Hi, I too am applying practice theory ( to understand entrepreneurial opportunity and collective identity construction in start-up teams) and have collected an array of data from ethnographic methods - namely; interviews, observations and documentation. I also am wondering what the conventions are for data analysis in PT and/or interesting novel approaches aside from thematic analyis?
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What is the proportion of the ekphrastic text to the source picture?
How enargia is discernible in an ekphrastic text?
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Only after almost a year that I came across your intelligent question. It made me ponder on the difference between typical ekphrastic poems like W. H. Auden's famous poems " Musée des Beaux Arts" & "The Dance" both of which are based on the paintings of Pieter Bruegel on one hand and the other, poems regarded as ekphrastic like John Keats's "Ode on a Grecian Urn" or Robert Browning's "My Last Duchess". The difference is the ability to associate verse with existing painting while in Keats and Browning it is only imaginary.
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Hi,
I am interested in semantic dementia and I am looking for database/repository of narrative speech transcripts of patients suffering from semantic dementia, or conversations with patients with semantic dementia.
I have found very short ones such as here
but I am looking for larger databases, whatever the language is
Thanks a lot,
Josselin Houenou (Mondor Univ. Hospital, Psychiatry Dept, Créteil, France)
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hi Josselin
NCBI database
If you want help, I am at your service
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Hello everybody.
I am preparing a review on a "broader" question about socioeconomics and I am having difficulties distinguishing between a scoping review and a narrative systematic review.
I hope somebody have some comments on this.
Thank you.
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Hello,
A few years ago, the center I direct, the Center on Knowledge Translation for Disability and Rehabilitation Research (Center on KTDRR) did a training on scoping review methods that may be helpful to you. It is archived here: https://ktdrr.org/training/workshops/scoping/
The Joanna Briggs Institute has also published a how-to manual on scoping reviews:
Good luck with your project!
Kathleen
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The health care system is facing challenges when more individuals are not taking responsibility over their own health care decisions and actions. This is evident in narratives where patient decline medicine, missed appointments, and non-adherence to suggested treatments.
Will it be ethically appropriate to demand that patients assume increased responsibility for their own health e.g. adherence to treatments and care?
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Yes, it will be, mainly about his disease, as on diet and other etiologic factors and the probable dangers.
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I used a variety of theory to construct a series of questions related to Trust and received over 10 valid responses. I used the usual statistical analytical methods to understand the underlying factors. The questionnaire also had a section asking for narrative comments about different aspects of trust. I developed a coding scheme to analyze this section. I can characterize the narratives in terms of frequency distributions. However, I need guidance on how I can statistically relate the quantitative and qualitative/narrative sections of the responses. I've been down several rabbit holes and need definitive guidance on how I can resolve my problem...
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I think that the content analysis method can do that, provided the tool is designed meticulously, and it contains all the fixed and variable elements
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I'm interested in seeing if anyone has used this a theoretical framework, and if so how?
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Diachronic Narratology. (The Example of Ancient Greek Narrative)
Irene J. F. de JongCreated: 4. September 2013Revised: 24. January 2014📷📷
Definition
1Diachronic narratology means the description and analysis of the history of the forms and functions of narrative devices within a given (period of a) literature.
Explication
2An explicit plea for the diachronization of narratology was launched by Fludernik (2003), although before her others, e.g. Pavel (1996), had in actual practice combined literary history and structuralist analysis. With this term, Fludernik does not mean the historiography of narratology itself, i.e. the history of the development of theoretical concepts, but the history of the actual use made by authors of narrative devices. What is the history of the first-person novel, of narratorial comments, of audience-address, of the locus amoenus, etc.? Some narrative devices have long been identified and studied, such as mimesis, the Muse, or openings, but narratology has brought together, systematised, and much expanded the number of narrative devices found employed by authors in narrative texts, and thereby opened the way to the study of their use over time.
History of the Concept and its Study
From Synchronic to Diachronic Narratology
3Classical narratology, a product of formalism and structuralism, almost is by definition synchronically rather than diachronically oriented. Its interest is the narrator in the text rather than the historical author producing that text, the narratees rather than flesh-and-blood readers, and the common signifying structures of narratives across time and space. Thus early narratology could perhaps be called ‘achronic’ rather than synchronic: it explicitly tried to elide extra-textual time and historical context in order to find the common ground of all narratives and get away from the traditional biographical fashion of literary criticism. As a result, there was for a long time, as Fludernik (2003: 331) noted, “comparatively little interest on a theoretical level in the history of narrative forms and functions.”
4Of course, there always have been narratological studies with historical dimensions. We may think here of Booth ([1961] 1983), which deals with the shift from overt to covert narrators in the 19th century; Romberg (1962), which discusses first-person novels from different countries and ages; or Scholes and Kellogg ([1968] 2006), which includes historical studies on point of view, plot, and character in European narrative from antiquity onwards. And of course, before the advent and spread of narratology, classic historical studies on aspects of narrative were written e.g. by Auerbach ([1946] 2003), who deals with the representation of reality in European narrative, or Curtius ([1948] 1953), who traces the continuity of a.o. narrative devices like the Muse from Classical Latin via Medieval Latin into modern European literatures.
5But what put diachrony more emphatically on the agenda in the 1990s were, according to Fludernik (2003: 332), feminist narratology, the application of narratology to historical texts, and research into the origins of the novel. As an example of diachronic narratology, she discusses the handling of scene shifts in a corpus of some fifty texts of British literature between the late medieval period and the early 20th century. In her conclusion she notes that “the scene shift was ideally suited to demonstrate that formal analysis needs to be complemented by a functional approach [...] a function can be superseded and its former expressions still used for new purposes” (344).
6At about the same time that Fludernik was launching the idea of diachronic narratology, de Jong started—independently—editing a history of ancient Greek narrative. The need for such a history arises from the fact that while there are many histories of Greek drama, historiography, rhetoric, or literary criticism, “the history of ancient Greek narrative is as yet untold” (de Jong et al., eds. 2004: xi).
7This history appears in a series of volumes entitled “Studies in ancient Greek narrative” (SAGN). The historical approach offers, for the first time, a major example of diachronic narratology in that it traces the history of various narrative devices for one literature in its entirety. In the case of ancient Greek literature, this covers a time span of twelve centuries (800 BC to 400 AD). So far, three volumes have appeared: on narrators, narratees, and narratives (de Jong et al., eds. 2004), on time (de Jong & Nünlist, eds. 2007), and on space (de Jong, ed. 2012). A fourth volume, on characterization, is currently in progress. The narrative devices discussed include overt versus covert narrators or narratees, primary versus secondary narrators and narratees, second-person narration, embedded narratives, analepsis and prolepsis, singulative, iterative and scenic narration, retardation, acceleration, setting versus frame, focalised space, description and ekphrasis, the thematic, symbolic, and psychological functions of space. The series is aimed at a larger readership than the community of classicists, and thus all passages are discussed in translation.
A History of Ancient Greek Narrative as an Example of Diachronic Narratology
Defining Ancient Greek Narrative
8When writing a history of narrative devices, the first question to answer is what actually constitutes a narrative in the literature under discussion. For SAGN, the following texts of ancient Greek literature have been included: purely narrative genres (epic, novel); what could be called applied narrative genres (historiography, biography, philosophy); narratives embedded in non-narrative genres (the mythological parts of lyric, hymn, and pastoral; the prologue and messenger-speeches of drama; the narrationes of oratory); and what Genette ([1972] 1980: 236–37) called pseudo-diegetic narratives, i.e. narratives with a suppressed narrator. He used this term in explicit reference to Plato’s philosophical dialogue Theaetetus 143 c, where the narrator says that he avoids the tag “and he said.” In addition to Plato’s dialogues, we can think of the so-called mimetic Idyls of Theocritus and the Eclogues of Virgil, poems that consist entirely of dialogue but that belong to genres that also have instances with a narrative frame and a narrator.
9To modern eyes, this corpus may seem both broad and restricted. It is broad in that it includes philosophy and historiography, text-types which nowadays are not necessarily in narrative form and would not normally be included in a literary history. However, it should be borne in mind that philosophy in antiquity usually takes the form of narrated dialogues. As for ancient historiography, this was invariably in narrative form due to the fact that the genre’s pedigree traces back to epic (cf. Strasburger 1972). It confirms Genette’s ([1991] 1993) and Cohn’s (1999) contention that historiography falls within the domain of narratology. At the same time, it contradicts Cohn’s call for a separate historiographic narratology: in antiquity the same devices are found in semi-historical epic, historiography, and in the fictional novel.
10The SAGN corpus is restricted in that only narratives embedded in lyric and drama are included. Recently, some narratologists have argued that drama and lyric as a whole should be considered forms of narrative (see e.g. Jahn 2001; Hühn & Kiefer 2005; Hühn & Sommer → Narration in Poetry and Drama). In SAGN, however, the presence of a narrator is taken as the defining element of a narrative.
Form and Function of Narrative Devices
11One of the central research questions of diachronic narratology is that of the relationship between form and function: how does one and the same device acquire ever new functions, depending on the exigencies of a genre, the predilections of an author, the theme of the narrative, or the taste of an age?
12Since the greater part of ancient Greek narrative deals with the same mythological stories time and again, a beginning in medias res works differently in such a narrative whose content is largely known to the narratees (e.g. the Odyssey) than it does in a purely fictional text like Heliodorus’ Aethiopica. Anticipating the death of a hero may have a tone which is tragic (Iliad: Patroclus), moralistic (Odyssey: the suitors) or revengeful (Herodotus’ Histories). Drawing in the past in the form of external analepses may have a purely informative function (Homer: Iliad) or it may serve ideological purposes, the past being inserted for comparative reasons (Thucydides’ Peloponnesian War or Plutarch’s Biographies). The anachronical order in which many mythological stories are told in Greek literature (a narrator starts in the present, returns step by step to the past and then proceeds in chronological order back to the present) began as an oral device in Homer but was put to highly sophisticated use by Pindar and Sophocles in their lyric narratives. Greek literature has a long history of charging details of spatial setting with (ever-changing) semantic significance: thus when Plato for once situates one of his philosophical dialogues outside the city of Athens in the countryside (the Phaedrus), this setting has all the characteristics of a locus amoenus (trees, water, shade, a breeze); such a décor is typically the place for love-making, but is now refunctionalised to become the setting for a philosophical talk about love.
Genres and Development
13In ancient Greek narrative the use of narrative devices is not genre-bound: historians use epic devices, tragedians use historiographical devices, orators use tragic devices, and so on. This phenomenon can perhaps be explained as the result of genres being only loosely defined in ancient Greek literature (see e.g. Depew & Obbink, eds. 2000), but it also indicates the tendency of narrative devices to be universal. What can change, of course, is the function a device acquires in a given genre (see previous section).
14The history of ancient Greek narrative makes clear that literature need not necessarily develop in an evolutionary sense, i.e. in the form of a primitive origin slowly evolving towards ever more sophistication and complexity. Greek literature starts with a ‘big bang’, namely the Homeric epics with their incredibly rich and subtle exploitation of the potential of narrative, and ends with often rather simplistic novels. A caveat here is that for us, Homer’s texts are the first in ancient Greek literature, but that they were in fact preceded by innumerable oral predecessors whose texts have not come down to us, so that Homer was not really the first. There is also the intriguing issue of the indebtedness of early Greek literature to Near Eastern literature (see e.g. West 1997; Haubold 2013). But even taking these two observations into account, it is noteworthy that the text which is the fountainhead of all ancient (and much later European) narrative comes so early in history.
Narratology and (Oral) Poetry
15Narratology has developed primarily in connection with the novel and hence with prose narrative. In classics, however, narratological studies took poetry, especially epic poetry, into account from an early stage onwards (e.g. Fusillo 1985; de Jong [1987] 2004, 2001; Richardson 1990). Poets such as Homer, Hesiod, Apollonius of Rhodes, Callimachus, Pindar, Bacchylides, the three tragedians Aeschylus, Sophocles, Euripides, the comedian Aristophanes, and Theocritus all form a vital part of the history of Greek narrative art. Indeed, it was a poet, Homer, who developed most of the classical narrative toolkit: the Muses, the in medias res technique, prolepsis and analepsis, embedded focalization, or the tale within the tale. Later prose authors took over and carried on with what was originally developed by this poet. The differences between poetic and prose narrative seem to lie more at the level of stylistics: poetry uses more epithets, metaphors, similes, etc.
16When dealing with orality, narratology has focused on fairytales (mostly in written transcription) or on conversational narration (Fludernik → Conversational Narration – Oral Narration). Once again, the Homeric epics, be they oral texts or texts still very close to oral traditions (on this much debated issue, see e.g. the overview in Amodio 2005), provided rich material for narratology. For instance, the repetition of words, lines, and scenes, a hallmark of oral poetry, can be well understood and appreciated in Homer when analysed in terms of the narratological category of rhythm (de Jong 1991). This oral text has exercised a tremendous influence on all later, written literature, and the unbroken continuum of orality is a telling harbinger for the principle of intermediality in narrative. Whereas narratologists, dealing mainly with modern literature, look for intermediality in the new media of our present age (e.g. Ryan, ed. 2004; Ryan → Narration in Various Media), ancient Greek literature also provides much fascinating material in this area. The Homeric epics were oral in that they were composed orally and listened to, while many other texts were aural, i.e. written by their author but listened to by their consumers rather than read: the lyrics of Sappho and Pindar, the narratives of Greek drama, and the many speeches of orators like Lysias or Demosthenes. Even when ancient Greek narrative was written, it often still breathed a spirit of orality in the form of ‘fingierte Mündlichkeit’, either because writing was deemed suspect (in the time of the historian Herodotus) or because of the strength of tradition (the extremely bookish epic narrator Apollonius of Rhodes posing as a bard in order to resemble his venerated model Homer).
Topics for Further Investigation
17One of the areas calling for further reflection and investigation is how exactly we are to evaluate the results of diachronic narratology. What are we observing when we see different authors using the same narrative device across time and space? Can we indeed draw up a history, or should we be content with making a typological comparison? Can we consider such correspondences a form of narratological intertextuality, i.e. can we imagine author X consciously following the example of author Y, or should we rather think in terms of narrative universals, i.e. assume that different authors may employ the same device independently?  Or should we allow for both possibilities?
18The first option would seem to be a priori plausible in the literature of ancient Greece where, as in Roman literature, imitatio and aemulatio were key concepts, where all authors up until the Hellenistic era were telling roughly the same mythological stories, and where its main canonical text, the Homeric epics, provided most of the narrative tricks of the trade.
19But what about diachronic narratology on a larger scale which would discuss resemblances in narrative technique between neighbouring literatures (e.g. the Greek and Near Eastern literatures of 1600–700 BC) or succeeding literatures (such as classical, medieval, and modern European literatures)? Can we still draw historical lines here and, if so, how should we imagine this to have worked in practice? Do authors pick up their narrative devices from other texts, or are they somehow present in a culture in the form of memes? Some first tentative thoughts on these matters are developed in de Jong (2014a and 2014b).
Bibliography
Works Cited
  • Amodio, Mark C., ed. (2005). New Directions in Oral Theory. Tempe: Arizona Center for Medieval and Renaissance Studies.
  • Auerbach, Erich ([1946] 2003). Mimesis, the Representation of Reality in Western Literature. Princeton: Princeton UP.
  • Booth, Wayne ([1961] 1983). The Rhetoric of Fiction. Chicago: Chicago UP.
  • Cohn, Dorrit (1999). The Distinction of Fiction. Baltimore: Johns Hopkins UP.
  • Curtius, Ernst R. ([1948] 1953). European Literature and the Latin Middle Ages. Princeton: Princeton UP.
  • Depew, Mary & Dirk Obbink, eds. (2000). Matrices of Genre. Authors, Canons, and Society. Cambridge: Harvard UP.
  • Fludernik, Monika (2003). “The Diachonization of Narratology.” Narrative 11, 331–48.
  • Fusillo, Massimo (1985). Il tempo delle Argonautiche. Un analisi del racconto in Apollonio Rodio. Roma: Edizioni dell’Ateneo.
  • Genette, Gérard ([1972] 1980). Narrative Discourse. An Essay in Method. Ithaca: Cornell UP.
  • Genette, Gérard ([1991] 1993). Fiction & Diction. Ithaca: Cornell UP.
  • Haubold, Johannes (2013). Greece and Mesopotamia: Dialogues in Literature. Cambridge: Cambridge UP.
  • Hühn, Peter & Jens Kiefer (2005). The Narratological Analysis of Lyric Poetry: Studies in English Poetry from the 16th to the 20th Century. Berlin: de Gruyter.
  • Jahn, Manfred (2001). “Narrative Voice and Agency in Drama: Aspects of a Narratology of Drama.” New Literary History 32, 659–79.
  • Jong, Irene J. F. de ([1987] 2004). Narrators and Focalizers. The Presentation of the Story in the Iliad. London: Duckworth.
  • Jong, Irene J. F. de (1991). “Narratology and Oral Poetry: The Case of Homer.” Poetics Today 12, 405–23.
  • Jong, Irene J. F. de (2001). A Narratological Commentary on the Odyssey. Cambridge: Cambridge UP.
  • Jong, Irene J. F. de (2014a). “After Auerbach. Ancient Greek Literature as Test Case of European Literary Historiography.” European Review 22,116–28.
  • Jong, Irene J. F. de (2014b). “The Anonymous Traveller in European Literature: a Greek Meme?” D. Cairns & R. Scodel (eds.). Defining Greek Narrative. Edinburgh: Edinburgh UP, 314–33.
  • Jong, Irene J. F. de et al., eds. (2004). Narrators, Narratees, and Narratives in Ancient Greek Literature. Studies in Ancient Greek Narrative 1. Leiden: Brill.
  • Jong, Irene J. F. de & René Nünlist, eds. (2007). Time in Ancient Greek Literature. Studies in Ancient Greek Narrative 2. Leiden: Brill.
  • Jong, Irene J. F. de, ed. (2012). Space in Ancient Greek Literature. Studies in Ancient Greek Narrative 3. Leiden: Brill.
  • Pavel, Thomas (1996). L’art d’éloignement. Essai sur l’imagination classique. Paris: Gallimard.
  • Richardson, Scott (1990). The Homeric Narrator. Nashville: Vanderbilt UP.
  • Romberg, Bertil (1962). Studies in the Narrative Technique of the First-Person Novel. Stockholm: Almqvist & Wiksell.
  • Ryan, Marie-Laure, ed. (2004). Narrative across Media: The Languages of Storytelling. Lincoln: U of Nebraska P.
  • Scholes, Robert & Robert Kellogg ([1968] 2006). The Nature of Narrative. Fortieth Anniversary Edition. New York: Oxford UP.
  • Strasburger, Herman (1972). “Homer und die Geschichtsschreibung.” Studien zur Alten Geschichte, Bd ii. Hildesheim: Georg Olms, 1057–97.
  • West, Martin L. (1997). The East Face of Helicon: West Asiatic Elements in Greek Poetry and Myth. Oxford: Oxford UP.
Further Reading
  • Fusillo, Massimo (1991). Naissance du roman. Paris: Seuil.
  • Grethlein, Jonas (2006). Das Geschichtsbild der Ilias. Eine Untersuchung aus phänomenologischer und narratologischer Perspektive. Göttingen: Vandenhoeck and Ruprecht.
  • Grethlein, Jonas & Rengakos, Antonios, eds. (2009). Narratology and Interpretation: The Content of Narrative Form in Ancient Literature. Berlin: de Gruyter.
  • Lowe, Nick J. (2000). The Classical Plot and the Invention of Western Narrative. Cambridge: Cambridge UP.
  • Wheeler, Stephen M. (1999). A Discourse of Wonders: Audiences and Performances in Ovid’s Metamorphoses. Philadelphia: U of Pennsylvania P.
  • Winkler, Jack J. (1985). Auctor and Actor: A Narratological Reading of Apuleius’ The Golden Ass. Berkeley: U of California P.
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Any recommended readings on narrative universals? I am familiar with works by Frazer, Olrik, Campbell, Brewer, Bischof, Burkert, Booker, Hogan, Sternberg, Neumann, and Witzel; but there might be useful work beyond those straightforward works on universal characteristics of human storytelling. Thus, any--even rather absurd--recommendations much appreciated ...
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The school that actually declared and pursued the ambition of identifying what you must be referring to by 'narrative universals' is that of European (or Parisian, or Greimassian) semiotics. Algirdas Julien (Julius) Greimas and his school developed what they called the narrative grammar. It's positivist and highly demanding, but very analytic, too. A good place to start and see if you want to take the effort is the comprehensive dictionary of semiotics: A. J. Greimas and J. Courtés, 'Semiotics and language: an analytical dictionary' ('Sémiotique: dictionnaire raisonné de la théorie du langage', 1979, in the original, translated into a number of languages including English).
The hermeneutic take on the issue has been performed by Paul Ricœur (in 'Time and Narrative') re-reading Aristotle. That's a completely different style of working and premises (sometimes in an open and very qualified debate with structuralism at large and Greimas specifically).
(Apologies if this is repetitive, I'm somehow failing to post it properly this time.)
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Historical novels or novels whose subject matter is about historical events like emigration or forced emigration. Tend to blend historical truth and fiction in their narrative, in this case the historic event serves as a background to, in some cases fictitious characters. This intersection I would like to know what is it i called or rather what might it be called?
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Nov 2, 2017 - Short stories, novels, myths, legends, and fairy tales are all considered fiction. While settings, plot points, and characters in fiction are sometimes ..
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I am a PhD student at the Free University of Amsterdam. My provisional research topic is "An Analysis of Bokyi Discourse Narrative and its Implications for translating the story of the call of Abraham in Genesis 12.
I want to find out how an understanding of Bokyi (my language) narratives can help in translating the story of the call of Abraham in a way that would be natural, clear, accurate, and acceptable to Bokyi people.
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I suggest you start with a theoretical framework to analyze the narrative construction of the texts you choose to examine. Think of Robert E. Longacre’s Text Generation and Text Analysis or his taxonomy regarding plot structure. Once you decide on a theoretical framework, you can then adapt it to examine patriarchal narratives or any other type. By the way, Longacre studies biblical discourses extensively and published papers as well as a book on the Joseph narrative.
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I am writing a review, and I wonder under what condition can we use sentences like "Approaches at ... have been discussed elsewhere[12-14]" or "More detailed information concerning ... could be found in Ref 12,13"?
I can not control the timing to say such words.
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If you are talking about peer review, you focus on areas of clarity, punctuations, grammar issues and lack of information. You put the paragraph and line numbers. You don't worry about whether a researcher's work was covered by anyone else. You information will either allow or disallow someone's someones paper to get into a journal, don't take that for granted.
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Introduction:
To preserve the memories of what really happened, and the devices artificially used to distort reality with the purpose to fit an internationally motivated political agenda, a study is proposed, not claiming for me to be able to even do it on my own, but with the purpose to stimulate or to motivate the willing and diligent honest researcher that is reading this, to do it on his or on their own, individually or as a group, especially now that innumerable authentic files are being deleted, that are being disappeared, and removed, as to keep on brainwashing humanity according to the official narrative that undertook with the most advanced science and technology, on the first place those attacks.
Hypotheses:
Ha: It is possible, by integrating in a 3-D model of as much videos and photos as possible of that day (9/11/01), to demonstrate that the tragedy that we saw on TV was something different than what we saw, that the supposed planes hitting the WTC were not planes at all but a combination of technologies to deceive the viewer into thinking that those were real planes.
Ho: It is possible, by integrating in a 3-D model of as much videos and photos as possible of that day (9/11/01), to demonstrate that the tragedy that we saw on TV was something that happened exactly as we saw it, and that the planes hitting the WTC were real planes and not a combination of technologies to deceive the viewer into a particular and sinister agenda.
Antecedents:
As an evidence that there is a perverse purpose to blot-out of the memory of humanity that raw reality of what happened on September the 11th of 2001, where three towers of the WTC were demolished on their footprint: WTC-1, WTC-2, WTC-7, I will put just one example, the Archive dot org, a place supposedly in existence to preserve the memories of what really happened in the past and right now, refuses to keep a memory of one of the heroes of 9/11 because he, a millions of others, is able to think and to refute the absurd official narrative filled with inconsistencies and with nonsensical rhetoric: William Rodriguez. I needed to go to an Archive dot is, from Iceland, in order to take a glimpse of his, now extinct, website.
There was a whistleblower in its proper day who declared that the real planes supposedly responsible for hitting the twin towers and the other targets (The Pentagon and a piece of land in Shanksville, PA), in the photos I remember having seen him a white male with golden hair, a little chubby, but that information has disappeared (I just found some of it: https://www.youtube.com/watch?v=B2QAh0rBrew, and I think that the voice is that of Dylan Avery, the one that did "Loose Change", the first Internet Documentary Blockbuster denouncing some of the lies of 9/11), or if it still exist, Google and any other possible search engine are in the purpose of making harder and harder to find key information denouncing the legitimacy of the official narrative.
So, because we do not want that to happen with the rest of the information that is still kept in one place or another, even if many original sites have disappeared, the proposal to integrate in a 3-D model every single piece of footage showing a plane from a distinctive angle hitting the towers of the WTC, will be vital for this research....
Basic References for Now (This list will obviously grow to sizes still do not fathomed at this point):
https://www.youtube.com/watch?v=T_ssENU8OAw (In this movie, the aspects that I investigated in due time appear in minutes 2:06:22 to 2:17:44; https://pubmed.ncbi.nlm.nih.gov/21743816/, Figs. 2 and 4, always seeking the truth to be known, NOT at all a personal recognition)
Expectations:
First, to preserve the original footage that was sold to the public as airplanes hitting the WTC, that with the technology from now on, can be seen as fake inputs into the videos (please, check very carefully the first two links, and from the second, after the times given, which is where the focus lies on fake planes). So many books and movies have been already done about the travesty that the official story told by the US Government since that day, until now, and by a completely corrupt Mass Media, that this research is just another humble suggestion, one more nail for that coffin, that at least, has the minimum expectation to alert and to open the eyes of those that are still asleep into thinking that the narrative forced upon us with violence is the right one...
Additional sequences to explore are:
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I fully agree with Fernando Castro-Chavez
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Can System dynamics simulate cash transfer narratives well, If we consider multiple factors such as education, health and economy?
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Are there any reasons for writing classical narrative reviews rather than systematic ones?
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Great answers!
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I am interested in using literature narratives for social research
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I would submit the novel "Gravity's Rainbow" by Thomas Pychon as an example of the influence of technology on the lives of people during WWII. An influence that has only gained momentum in its outsized ability to perturb our very existence today. Another example would be the science fiction novels of James Blish, specifically the "Cities in Flight" series of novels that begins with "They Shall Have Stars" and finishes with "The Triumph of Time". These novels coopt John Steinbeck's okies, who presaged the gig workers in our economy of today.
Regards,
Tom Cuff