Things we are aware of and understand.
It is possible that authors did not identify, want to identify, or acknowledge potential limitations or were unaware of what limitations existed. Cumulative complexity is the result of the presence of multiple limitations because of the accumulation and interaction of limitations and their components. Just mentioning a limitation category and not the specific parts that are the limitation(s) is not enough. Authors telling readers of their known research limitations is a caution to discount the findings and conclusions. At what point does the caution for each limitation, its ramifications, and consequences become a warning? When does the piling up of mistakes, bad and missing data, biases, small sample size, lack of generalizability, confounding factors, etc., reach a point when the findings become s uninterpretable and meaningless? “Caution” indicates a level of potential hazard; a warning is more dire and consequential. Authors use the word “caution” not “warning” to describe their conclusions. There is a point when the number of limitations and their cumulative effects surpasses the point where a caution statement is no longer applicable, and a warning statement is required. This is the reason for establishing a limitations risk score.
Limitations put medical research articles at risk. The accumulation of limitations (variables having additional limitation components) are gaps and flaws diluting the probability of validity. There is currently no assessment method for evaluating the effect(s) of limitations on research outcomes other than awareness that there is an effect. Authors make statements warning that their results may not be reliable or generalizable, and need more research and larger numbers. Just because the weight effect of any given limitation is not known, explained, or how it discounts findings does not negate a causation effect on data, its analysis, and conclusions. Limitation variables and the ramifications of their effects have consequences. The relationship is not zero effect and accumulates with each added limitation.
As a result of this research, a limitation index score (LIS) system and assessment tool were developed. This limitation risk assessment tool gives a scores assessment of the relative validity of conclusions in a medical article having limitations. The adoption of the LIS scoring assessment tool for authors, researchers, editors, reviewers, and readers is a step toward understanding the effects of limitations and their causal relationships to findings and conclusions. The objective is cleaner, tighter methodologies, and better data assessment, to achieve more reliable findings. Adjustments to research conclusions in the presence of limitations are necessary. The degree of modification depends on context. The cumulative effect of this burden must be acknowledged by a tangible reduction and questioning of the legitimacy of statements made under these circumstances. The description calculating the LIS score is detailed in Appendix 1 .
A limitation word or phrase is not one limitation; it is a group of limitations under the heading of that word or phrase having many additional possible components just as an individual named influence. For instance, when an admission of selection bias is noted, the authors do not explain if it was an exclusion criterion, self-selection, nonresponsiveness, lost to follow-up, recruitment error, how it affects external validity, lack of randomization, etc., or any of the least 263 types of known biases causing systematic distortions of the truth whether unintentional or wanton. 40 , 76 Which forms of selection bias are they identifying? 63 Limitations have branches that introduce additional limitations influencing the study’s ability to reach a useful conclusion. Authors rarely tell you the effect consequences and extent limitations have on their study, findings, and conclusions.
This is a sample of limitations and a few of their component variables under the rubric of a single word or phrase. See Table 3 .
A Limitation Word or Phrase is a Limitation Having Additional Components That Are Additional Limitations. When an Author Uses the Limitation Composite Word or Phrase, They Leave out Which One of Its Components is Contributory to the Research Limitations. Each Limitation Interacts with Other Limitations, Creating a Cluster of Cross Complexities of Data, Findings, and Conclusions That Are Tainted and Negatively Affect Findings and Conclusions
Small Sample Size | Retrospective Study | Selection Bias |
---|---|---|
Low statistical power | Missing information | Affects internal validity |
Estimates not reliable | Recall bias | Nonrandom selection |
Prone to biased samples | Observer bias | Leads to confounding |
Not generalizable | Misclassification bias | Not generalizable |
Prone to false negative error | Observer bias | Inaccurate relation to variables |
Prone to false positive error | Evidence less robust than prospective study | Observer bias |
Sampling error | Missing data | Sampling bias |
Confounding factors | Volunteer bias | |
Selection bias | Survivorship bias |
Limitations rarely occur alone. If you see one there are many you do not see or appreciate. Limitation s components interact with their own and other limitations, leading to complex connections interacting and discounting the reliability of findings. By how much is context dependent: but it is not zero. Limitations are variables influencing outcomes. As the number of limitations increases, the reliability of the conclusions decreases. How many variables (limitations) does it take to nullify the claims of the findings? The weight and influence of each limitation, its aggregate components, and interconnectedness have an unknown magnitude and effect. The result is a disorderly concoction of hearsay explanations. Table 4 is an example of just two single explanation limitations and some of their components illustrating the complex compounding of their effects on each other.
An Example of Interactions between Only Two Limitations and Some of Their Components Causes 16 Interactions
Retrospective Study | Small Sample Size |
---|---|
The novelty of this paper on limitations in medical science is not the identification of research article limitations or their number or frequency; it is the recognition of the multiplier effect(s) limitations and the influence they have on diminishing any conclusion(s) the paper makes. It is possible that limitations contribute to the inability of studies to replicate and why so many are one-time occurrences. Therefore, the generalizability statement that should be given to all readers is BEWARE THERE IS A REDUCTION EFFECT ON THE CONCLUSIONS IN THIS ARTICLE BECAUSE OF ITS LIMITATIONS.
Journals accept studies done with too many limitations, creating forking path situations resulting in an enormous number of possible associations of individual data points as multiple comparisons. 79 The result is confusion, a muddled mess caused by interactions of limitations undermining the ability to make valid inferences. Authors know and acknowledge but rarely explain them or their influence. They also use incomplete and biased databases, biased methods, small sample sizes, and not eliminating confounders, etc., but persist in doing research with these circumstances. Why is that? Is it because when limitations are acknowledged, authors feel justified in their conclusions? It wasn’t my poor research design; it was the limitation(s). How do peer reviewers score and analyze these papers without a method to discount the findings and conclusions in the presence of limitations? What are the calculus editors use to justify papers with multiple limitations, reaching compromised or spurious conclusions? How much caution or warning should a journal say must be taken in interpreting article results? How much? Which results? When? Under what circumstance(s)?
Since a critical component of research is its limitations, the quality and rigor of research are largely defined by, 75 these constraints making it imperative that limitations be exposed and explained. All studies have limitations admitted to or not, and these limitations influence outcomes and conclusions. Unfortunately, they are given insufficient attention, accompanied by feeble excuses, but they all matter. The degrees of freedom of each limitation influence every other limitation, magnifying their ramifications and confusion. Limitations of a scientific article must put the findings in context so the reader can judge the validity and strength of the conclusions. While authors acknowledge the limitations of their study, they influence its legitimacy.
Not only are limitations not properly acknowledged in the scientific literature, 8 but their implications, magnitude, and how they affect a conclusion are not explained or appreciated. Authors work at claiming their work and methods “overcome,” “avoid,” or “circumvent” limitations. Limitations are explained away as “Failure to prove a difference does not prove lack of a difference.” 60 Sample size, bias, confounders, bad data, etc. are not what they seem and do not sully the results. The implication is “trust me.” But that’s not science. Limitations create cognitive distortions and framing (misperception of reality) for the authors and readers. Data in studies with limitations is data having limitations. It was real but tainted.
Limitations are not a trivial aspect of research. It is a tangible something, positive or negative, put into a data set to be analyzed and used to reach a conclusion. How did these extra somethings, known unknowns, not knowns, and unknown knowns, affect the validity of the data set and conclusions? Research presented with the vagaries of explicit limitations is intensified by additional limitations and their component effects on top of the first limitation s , quickly diluting any conclusion making its dependability questionable.
This study’s analysis of limitations in medical articles averaged 3.9% per article for JSLS and 7.4% for Surg Endosc . Authors admit to some and are aware of limitations, but not all of them and discount or leave out others. Limitations were often presented with misleading and hedging language. Authors do not give weight or suggest the percent discount limitations have on the reliance of conclusion(s). Since limitations influence findings, reliability, generalizability, and validity without knowing the magnitude of each and their context, the best that can be said about the conclusions is that they are specific to the study described, context-driven, and suspect.
Limitations mean something is missing, added, incorrect, unseen, unaware of, fabricated, or unknown; circumstances that confuse, confound, and compromise findings and information to the extent that a notice is necessary. All medical articles should have this statement, “Any conclusion drawn from this medical study should be interpreted considering its limitations. Readers should exercise caution, use critical judgement, and consult other sources before accepting these findings. Findings may not be generalizable regardless of sample size, composition, representative data points, and subject groups. Methodologic, analytic, and data collection may have introduced biases or limitations that can affect the accuracy of the results. Controlling for confounding variables, known and unknown, may have influenced the data and/or observations. The accuracy and completeness of the data used to draw a conclusion may not be reliable. The study was specific to time, place, persons, and prevailing circumstances. The weight of each of these factors is unknown to us. Their effect may be limited or compounded and diminish the validity of the proposed conclusions.”
This study and findings are limited and constrained by the limitations of the articles reviewed. They have known and unknown limitations not accounted for, missing data, small sample size, incongruous populations, internal and external validity concerns, confounders, and more. See Tables 2 and and 3 . 3 . Some of these are correctible by the author’s awareness of the consequences of limitations, making plans to address them in the methodology phase of hypothesis assessment and performance of the research to diminish their effects.
Limitations in research articles are expected, but they can be reduced in their effect so that conclusions are closer to being valid. Limitations introduce elements of ignorance and suspicion. They need to be explained so their influence on the believability of the study and its conclusions is closer to meeting construct, content, face, and criterion validity. As the number of limitations increases, common sense, skepticism, study component acceptability, and understanding the ramifications of each limitation are necessary to accept, discount, or reject the author’s findings. As the number of hedging and weasel words used to explain conclusion(s) increases, believability decreases, and raises suspicion regarding claims. Establishing a systematic limitation scoring index limitations for authors, editors, reviewers, and readers and recognizing their cumulative effects will result in a clearer understanding of research content and legitimacy.
How to calculate the Limitation Index Score (LIS). See Tables 5 – 5 . Each limitation admitted to by authors in the article equals (=) one (1) point. Limitations may be generally stated by the author as a broad category, but can have multiple components, such as a retrospective study with these limitation components: 1. data or recall not accurate, 2. data missing, 3. selection bias not controlled, 4. confounders not controlled, 5. no randomization, 6. no blinding, 7. difficult to establish cause and effect, and 8. cannot draw a conclusion of causation. For each component, no matter how many are not explained and corrected, add an additional one (1) point to the score. See Table 2 .
The Limitation Scoring Index is a Numeric Limitation Risk Assessment Score to Rank Risk Categories and Discounting Probability of Validity and Conclusions. The More Limitations in a Study, the Greater the Risk of Unreliable Findings and Conclusions
Number of limitations | Word description of discounting | Proposed percent discounting of conclusions | Outcome probability | Increasing level of less reliable conclusions |
---|---|---|---|---|
0 | Unknown unknowns | 1–10% | May have valid conclusion(s) | Warning |
1–2 | Some | 15–25% | ↓ | ↓ |
3–4 | Probable | 35–45% | ↓ | Caution |
5–6 | Likely | 70–80% | ↓ | ↓ |
7–8 | Highly likely | 85–95% | ↓ | ↓ |
>8 | Certain | 97–100% | Very questionable conclusion(s) | Danger |
Limitations May Be Generally Stated by the Author but Have Multiple Components, Such as a Retrospective Study Having Disadvantage Components of 1. Data or Recall Not Accurate, 2. Data Missing, 3. Selection Bias Not Controlled, 4. Confounders Not Controlled, 5. No Randomization, 6. No Blinding, 7 Difficult to Establish Cause and Effect, 8. Results Are Hypothesis Generating, and 9. Cannot Draw a Conclusion of Causation. For Each Component, Not Explained and Corrected, Add an Additional One (1) Point Is Added to the Score. Extra Blanks Are for Additional Limitations
One point for each limitation | |
---|---|
One additional point for each component of each limitation | |
Retrospective study | |
Small sample size | |
Not generalizable | |
Selection bias | |
Not controlling for confounders | |
Not controlling for comorbidities | |
Incomplete or missing data | |
No long-term follow-up | |
Reporting errors | |
Measurement problems | |
Study design problems | |
Lack of standardized treatment | |
Subtotal for Table 2 |
An Automatic 2 Points is Added for Meta-Analysis Studies Since They Have All the Retrospective Detrimental Components. 44 Data from Insurance, State, National, Medicare, and Medicaid, Because of Incorrect Coding, Over Reporting, and Under-Reporting, Etc. Each Component of the Limitation Adds One Additional Point. For Surveys and Questionnaires Add One Additional Point for Each Bias. Extra Blanks Are for Additional Limitations
Two points for these limitations | |
---|---|
One additional point for each limitation and one additional point for each limitation component. | |
Meta-analysis | |
Data from Medicare, Medicaid, insurance companies, disease, state, and national databases | |
Surveys and questionnaires | |
Each limitation not admitted to | |
Subtotal for Table 3 |
Automatic Five (5) Points for Manufacturer and User Facility Device Experience (MAUDE) Database Articles. The FDA Access Data Site Says Submissions Can Be “Incomplete, Inaccurate, Untimely, Unverified, or Biased” and “the Incidence or Prevalence of an Event Cannot Be Determined from This Reporting System Alone Due to Under-Reporting of Events, Inaccuracies in Reports, Lack of Verification That the Device Caused the Reported Event, and Lack of Information” and “DR Data Alone Cannot Be Used to Establish Rates of Events, Evaluate a Change in Event Rates over Time or Compare Event Rates between Devices. The Number of Reports Cannot Be Interpreted or Used in Isolation to Reach Conclusions” 80
Five points for MAUDE based articles | |
---|---|
One additional point for each additional limitation and one point for each of its components. | |
Subtotal for Table 4 |
Total Limitation Index Score
Limitations | Calculation |
---|---|
Subtotal for Table 2 | |
Subtotal for Table 3 | |
Subtotal for Table 4 | |
Total Limitation Index Score |
Each limitation not admitted to = two (2) points. A meta-analysis study gets an automatic 2 points since they are retrospective and have detrimental components that should be added to the 2 points. Data from insurance, state, national, Medicare, and Medicaid, because of incorrect coding, over-reporting, and underreporting, etc., score 2 points, and each component adds one additional point. Surveys and questionnaires get 2 points, and add one additional point for each bias. See Table 3 .
Manufacturer and User Facility Device Experience (MAUDE) database articles receive an automatic five (5) points. The FDA access data site says, submissions can be “incomplete, inaccurate, untimely, unverified, or biased” and “the incidence or prevalence of an event cannot be determined from this reporting system alone due to underreporting of events, inaccuracies in reports, lack of verification that the device caused the reported event, and lack of information” and “MDR data alone cannot be used to establish rates of events, evaluate a change in event rates over time or compare event rates between devices. The number of reports cannot be interpreted or used in isolation to reach conclusions.” 80 See Table 4 . Add one additional point for each additional limitation noted in the article.
Add one additional point for each additional limitation and one point for each of its components. Extra blanks are for additional
limitations and their component scores.
Funding sources: none.
Disclosure: none.
Conflict of interests: none.
Acknowledgments: Author would like to thank Lynda Davis for her help with data collection.
All references have been archived at https://archive.org/web/
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The discussion section contains the results and outcomes of a study. An effective discussion informs readers what can be learned from your experiment and provides context for the results.
When you’re ready to write your discussion, you’ve already introduced the purpose of your study and provided an in-depth description of the methodology. The discussion informs readers about the larger implications of your study based on the results. Highlighting these implications while not overstating the findings can be challenging, especially when you’re submitting to a journal that selects articles based on novelty or potential impact. Regardless of what journal you are submitting to, the discussion section always serves the same purpose: concluding what your study results actually mean.
A successful discussion section puts your findings in context. It should include:
Tip: Not all journals share the same naming conventions.
You can apply the advice in this article to the conclusion, results or discussion sections of your manuscript.
Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts.
Questions to ask yourself:
Trying to fit a complete discussion into a single paragraph can add unnecessary stress to the writing process. If possible, you’ll want to give yourself two or three paragraphs to give the reader a comprehensive understanding of your study as a whole. Here’s one way to structure an effective discussion:
While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results!
Snippets of Effective Discussions:
Consumer-based actions to reduce plastic pollution in rivers: A multi-criteria decision analysis approach
Identifying reliable indicators of fitness in polar bears
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npj Antimicrobials and Resistance volume 2 , Article number: 16 ( 2024 ) Cite this article
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Antimicrobial resistance is a global threat to public health. Without proactive intervention, common infections may become untreatable, restricting the types of clinical intervention that can be undertaken and reversing improvements in mortality rates. Effective antimicrobial stewardship represents one approach to restrict the spread of antimicrobial resistance but relies on rapid and accurate diagnostics that minimise the unnecessary use of antibiotics. This is increasingly a key unmet clinical need. In this paper, we describe existing techniques for the detection of antimicrobial resistance, while examining their drawbacks and limitations. We also discuss emerging diagnostic technologies in the field, and the need for standardisation to allow for swifter and more widespread clinical adoption.
Introduction.
Since the introduction of penicillin during World War II, antibiotics have become the backbone of modern medicine 1 , 2 . The success of antibiotics resulted in a golden age in medicine, but this is now coming to an end as we risk entering a post-antibiotic era. A lack of effective antibiotics reduces our capacity to respond to outbreaks of infectious disease. Without coordinated, proactive interventions to detect and manage antimicrobial resistance (AMR), there will be a significant regression in medical care and a steep increase in mortality rates 3 . Many modern medical techniques are dependent on the availability of effective antimicrobials, without them many common procedures and interventions (cancer chemotherapy, organ transplantation, prosthetic joint replacement etc) may not be able to be undertaken without excess risk 3 .
Multi-drug resistant organisms (MDROs) are the outcome of years of antibiotic dependency in medical practice and are responsible for an increasing number of infections. MDRO are categorised by three increasing resistance levels 4 :
Multidrug-resistant (MDR) – nonsusceptibility to at least one agent in three or more antimicrobial agent classes.
Extensively drug-resistant (XDR) – nonsusceptibility to at least one agent in all but two (or fewer) antimicrobial agent classes.
Pan drug-resistant (PDR) or sometimes referred to as totally drug-resistant (TDR) whereby the organism shows nonsusceptibility to all agents in all classes.
MDROs are considered a global crisis affecting low, middle and high-income countries 5 , given their potentially untreatable nature 6 . AMR does not respect borders, neither geographical nor ecological, and with the use of antimicrobials in food producing animals we are seeing transmission of resistant pathogens from livestock into humans 7 . In 2015, the Global Action Plan on Antimicrobial Resistance was established by the World Health Assembly to address the threat of AMR 5 , 8 . This was followed by the United Nations General Assembly that passed a resolution unanimously calling for a globally coordinated action resulting in the One Health approach to AMR 5 , 9 , 10 . The One Health approach is a multidisciplinary joint effort to provide solutions for human, animal, and environmental health 11 .
The socioeconomic burden of AMR is difficult to gauge but known to be significant. Mortality estimates range from 0.7–4.95 million deaths worldwide annually, and healthcare costs amounting to tens of billions of US dollars 8 , 10 , 12 , 13 , 14 . It is likely that these numbers are an underestimate due to insufficient national reporting rates, a lack of comprehensive data coverage and no International Classification of Diseases (ICD-10) code specifically for MDRO infections 15 . In 2018, Burnham et al. re-analysed the 2010 data for MDRO-related deaths in the US, identifying 154,113 deaths vs an original estimation of 23,000, nearly seven times the original CDC estimate 15 . What we do know, is that MDROs are on the rise, with the number of reported MDR strains quadrupling over the last two decades, particularly in young children, accounting for 5–10% hospitalised cases 16 , 17 , 18 .
With the world population now around 8 billion and over 55% of all people concentrated in densely populated urban centres 19 ; the risk of a bacterial pandemic is increasingly likely without effective control 20 . The COVID-19 pandemic has been a stark reminder of the ferocity at which an infectious disease can spread and the extensive damage it can cause 21 . Surveillance of infectious agents must improve to allow us to better prepare for and limit future outbreaks, reducing our dependency on antibiotics. Furthermore, tracking how, where, and at what rate antibiotic resistance is evolving in bacteria, can aid in predicting and fighting outbreaks of AMR infections. Currently, patients with suspected infections are most likely to be treated empirically, with some countries estimating 30–50% inappropriate or unnecessary antibiotic usage 22 . This is disappointing considering the significant progress that has been made towards fast, accurate, and affordable diagnostics and the availability of antimicrobial resistance screening.
The European Committee on Antimicrobial Susceptibility Testing (EUCAST) and the Clinical Laboratory Standards Institute (CLSI) recommend investigating bacterial resistance to antibiotics using culture-based techniques 23 , 24 , 25 : the current gold standard for verifying AMR. Culture-based assessment involves observing and reporting the growth (or absence of growth) of bacteria exposed to various concentrations of antibiotics (Table 1 ). Culture-based approaches can be used to establish a minimum inhibitory concentration (MIC) or minimum bactericidal concentration (MBC) for a particular organism-antibiotic combination, giving an indication of the likelihood that a particular agent will be clinically effective. The main advantage of assessing AMR this way is the low cost, as the consumables and equipment are inexpensive compared to PCR 26 , 27 . However, some scientists argue that this labour intensive and slow approach is too costly both in terms of laboratory staff costs and extended in-patient times 26 . Less labour-intensive culture methods do exist, such as Disk and Strip diffusion gradient, but these are still time-costly and laborious to perform when testing multiple samples and antibiotics.
Culture-based assessment relies on the ability to isolate the strain of interest from a complex mixture, and it is also essential that the species is compatible with the culturing technique (e.g. anaerobic bacteria cannot grow in normal atmospheric conditions). To identify strains, a sample is initially grown on solid media and any colonies that form can be identified using a variety of techniques; amplification and sequencing based (16 S and PCR), biochemically (Analytical profile index, API), immunologically (Enzyme-linked immunosorbent assay, ELISA), or through protein fragment analysis using matrix-assisted laser desorption/ionisation time-of-flight mass spectrophotometry (MALDI-TOF MS) 28 . Once the species is/are identified, the antimicrobial susceptibility can be determined. Complex and non-sterile sample types such as faeces make the culture-based assessment difficult, as a plethora of colonies will grow during the initial culturing step. Selective media can be used in this case to target recovery of a suspected microbe of concern 29 .
Lateral flow tests (LFTs) can be used in the context of AMR assessment, the technology uses an immunochromatographic strip impregnated with antibodies to detect key enzymes associated with antimicrobial resistance e.g. beta-lactamase. LFTs proved highly successful during the COVID-19 pandemic 30 , 31 . However, LFTs have limited use in the context of AMR testing, as there is currently a requirement to first undertake pre-culture step 24 . So, while quick, LFTs are still limited by bacterial growth times and the capacity to undertake these steps 32 .
Molecular techniques for pathogen detection and antibiotic resistance mechanisms are an attractive alternative to culture-based methods due to their high selectivity at the RNA/DNA level, sensitivity, and ability to provide earlier identification (or diagnosis) 24 , 33 , 34 . While molecular methods are more expensive than culture-based ones (cost per test), one could argue that the benefit of earlier diagnosis, patient discharge from hospital, and fewer working days lost, presents cost savings in the wider context 26 .
Nucleic acid amplification tests (NAATs) for detection of pathogens can use a variety of amplification methods (PCR, Strand Displacement Amplification (SDA), Transcription-Mediated Amplification), but are mainly limited to PCR for antibiotic resistance gene detection 24 . PCR species identification is highly targeted and requires a level of empirical insight from medical professionals to narrow down the range of causative agents to direct screening. This is also true for AMR – the mechanism of resistance in the pathogen of interest must be known to allow for the design of targeted PCR primers. This is where whole genome sequencing (WGS) presents a huge advantage as it can identify bacteria as well as detect the presence of any AMR genes without prior knowledge 35 , and potentially without the need to culture.
Not all molecular techniques utilize nucleic acids as their form of detection, MALDI-TOF MS investigates the molecular composition of proteins and peptides within a sample. It identifies specific biomarkers based on their mass-to-charge ratio, providing information about the samples molecular profile 36 . This information used in conjunction with a reference database can be used to determine the identity of a pathogen and its AMR profile 37 . MALDI-TOF provides a comprehensive result with the potential to highlight multiple resistance mechanisms, however, this style of analysis can miss certain types of resistance that are not directly related to protein expression, such as mutations in regulatory regions or modifications in non-proteinaceous components of bacteria.
Third generation WGS systems provide long reads at high speed, examples being Illumina MiniSeq & MiSeq, and Oxford Nanopore’s MiniON and PromethION 24 , 38 . These systems permit rapid pathogen identification and antibiotic resistance in a single assay without a culturing step. There is ever growing support in the AMR surveillance field that these WGS methods could replace current phenotypic assays 35 , 39 , 40 , 41 .
To identify which AMR genes are present post-sequencing requires two bioinformatic components: an aligner (e.g. Resistance Gene Identifier (RGI) 39 , AMRFinderPlus 42 and ResFinder 43 ) and a database of known AMR gene sequences and their associated resistance phenotype (e.g. Comprehensive Antibiotic Resistance Database (CARD) 39 , MegaRes 44 and National Database of Antibiotic Resistant Organisms (NDARO) 45 ). WGS analysis provides speed, flexibility, and breadth as clinical samples can be screened against hundreds of potential resistance profiles simultaneously – a process that would be too laborious and excessively time consuming for culture-based approaches. Furthermore, sequencing is neither dependent on pure cultures nor on being able to culture fastidious strains. WGS has great potential for AMR surveillance and diagnosis, but it is not a routine clinical application. Unlike direct phenotypic testing, sequencing predictions only indicate the presence (or absence) of antibiotic resistance sequences in the sample. Clinical and phenotypic information is usually required in order to properly interpret the outputs of sequencing. The presence of an AMR gene does not necessarily translate to antibiotic resistance since the genes may be inactive, an area where MALDI-TOF provides greater certainty of an active resistance owing to its detection of proteins that could be linked to a resistance genes expression 37 . Of greater concern is the observation that, the absence of any AMR indicator genes may not always correctly infer phenotypic susceptibility, a documented example of this can be found in the false negative predictions by WGS in Salmonella enterica 46 .
In 2017, EUCAST highlighted several issues that need to be addressed before the technology can move forward in the clinical context 47 . The key points were:
There is a lack of evidence for the AMR gene prediction accuracy for many bacteria.
It is a non-trivial process to establish the equivalent of clinical breakpoints in genomic predictions.
No standardisation of bioinformatics tools and approach to perform quality control (QC).
There is no single database of all known resistance genes/mutations - multiple databases developed independently means again that there is no harmonisation and data output is not equivalent.
Nevertheless, the cost of sequencing is coming down and the move towards high throughput methodologies is progressing, meaning that the current barriers to entry are reducing 48 . We are already seeing a strong push towards WGS/NGS sequencing in other diagnostic fields (e.g. genetic disorders) and the value it would add to AMR surveillance and evidence-based drug prescription is significant 49 , 50 . The creation of standards, both written and physical reference reagents, in this growing field would help to address many of the concerns of EUCAST and help to accelerate wider acceptance.
To discuss how the different tools (Table 2 ) perform, we have chosen to highlight real world examples of where screening for antimicrobial resistance is essential or a growing concern:
Blood and CSF samples are commonly used to diagnose bacterial infections, as healthy individuals harbour no bacteria from these sample sites. The normally sterile nature of CSF and blood in these sample sites makes them ideal samples for pathogenic strain detection and identification, as there is no bacterial background against which a pathogen needs to be distinguished from. Nevertheless, despite their diagnostic advantages, there often arises an urgent necessity to treat diseases associated with these samples, such as sepsis or numerous neonatal infections, due to their potentially life-threatening nature. Earlier and effective treatment results in better clinical outcomes, especially in younger patients who are at greater risk from bacterial infections 51 , 52 , 53 . It is standard practice for clinicians to begin empiric antibiotic treatment prior to receiving information on bacterial susceptibility.
A clinical example of CSF usage is Bacterial meningitis, a highly lethal disease 54 , 55 . Initial empirical treatment is often necessary with CSF samples taken prior to enable informed diagnosis. CSF culture is considered the gold standard; however, PCR is increasingly becoming relied upon because of its far greater sensitivity 55 . It is difficult to employ AMR stewardship, when delays in treatment can cause deaths, but we are beginning to see the results of this with third-generation antibiotics (e.g. ceftriaxone) becoming ineffective against Escherichia coli meningitis 56 . The high mortality rate associated with these infections means it is essential we try to move towards faster diagnostic tools to provide early, effective treatment based on evidence (reliable clinical laboratory test results). An ONT (Oxford Nanopore Technologies)-based approach to WGS and rapid diagnostics in blood infections is considered very promising with high accuracy and fast turnaround results, with the potential to be applied to CSF and implemented in clinical settings 57 .
STIs are a global problem, with the highest burden in low- and middle- income countries (LMICs). When left untreated, STIs can cause complications ranging from problems with fertility and pregnancy to cancer 58 . The most common bacterial STIs are Chlamydia trachomatis and Neisseria gonorrhoeae (inferred from Public Health England data 59 ). Treponema pallidum (syphilis) , Haemophilus ducreyi (Chancroid), and Mycoplasma genitalium infections are also prevalent but occur at a far lower frequency 59 .
The relatively few causative bacterial agents associated with STIs makes targeted NAAT-based diagnostics an effective solution for infection identification. Furthermore, the characterisation of common AMR causing genes found in C. trachomatis and N. gonorrhoeae , also lend themselves well to NAAT-based AMR detection 24 , 60 , 61 , 62 and the preferred laboratory method for these two strains has shifted from culture 63 to NAAT 64 increasing sensitivity and specificity, and faster turnaround time 63 . WGS offers an alternative that would be able to strain ID and screen for AMR at the same time (and rapidly), but the high incidence would be too expensive in comparison to NAAT. However, given the rise in novel AMR causing genes it may become necessary in the future. Indeed, “super” gonorrhoea is already a growing AMR concern, with the first case of drug resistant gonorrhoea reported in London in December 2021 65 and a further two cases in the UK as of the 7 th February 2022 and increasing numbers across Europe 66 . The World Health Organisation (WHO) has launched a global action plan to control the spread and impact of antimicrobial resistance in N. gonorrhoeae as part of a wider STI surveillance plan, with a focus on controlling antibiotic usage and disease spread.
UTI infections are the most common infectious disease after respiratory tract infections and are a major public health problem in terms of morbidity and financial cost 67 . There has been an alarming rise in UTI antimicrobial resistance, likely owing to UTI patients being among the top receivers of outpatient antibiotic prescriptions 67 , 68 . The leading cause of UTI’s is uropathogenic Escherichia coli (UPEC), making up 80% of infections in women aged 18–39 69 , 70 . The current leading approach to identification and antibiotic susceptibility is culture-based screening. Given the overwhelming amount of UPEC caused infections and the small bacterial background of the sample one could argue for the use of lateral flow or multiplex PCR to confirm presence of E. coli and its resistance profile. Although neither of these approaches would rule out other organisms, they provide a far more rapid diagnosis of the leading cause. There is a growth of emerging technologies in UTI diagnostics, utilising microfluidics and lab-on-a-chip concepts to help provide point of care species identification and treatment suggestions 71 , 72 .
Respiratory tract infections are a major global health issue, especially in low-income countries with limited healthcare access. Additionally, outbreaks of highly contagious respiratory infections, can have far-reaching consequences on a global scale, causing widespread illness, economic disruption, and loss of life. Efforts to prevent, detect, and effectively manage respiratory tract infections are crucial for safeguarding public health and minimising their impact. Pathogens commonly causing respiratory infections include Streptococcus pneumoniae , Haemophilus influenzae , Mycoplasma pneumoniae , Pseudomonas aeruginosa , and Mycobacterium tuberculosis 73 . Antibiotics are used to manage these infections with over half of all UK oral antibiotic prescriptions being written for this indication 74 . Several mechanisms conferring antimicrobial resistance in the organisms listed above have been observed and are of increasing concern 73 , 74 . A recent study describes the life cycle of antibiotic resistance genes in Pseudomonas aeruginosa isolated from hospitalised, ventilated patients 75 . They demonstrate the value of using targeted sequencing to identify and track AMR genes, showing that the data generated can inform treatment by enabling patient-specific antibiotic cycling strategies.
Pulmonary tuberculosis (TB) can be transmitted between individuals and is a significant contributor to poor health and mortality rates globally. Prior to the COVID-19 pandemic, TB held the unfortunate distinction of being the leading cause of death among single agent infectious diseases, surpassing even HIV/AIDS in its impact 76 . Culture of sputum of other respiratory secretions is considered the gold standard for diagnosis, however, it is slow-growing, taking two to six weeks for culture and an additional three plus weeks for multi-drug resistance testing 77 . Rapid detection of resistance patterns and prompt initiation of appropriate treatment are essential for effectively controlling TB and minimising the transmission of drug-resistant strains 78 . Faster diagnostic and susceptibility assays already exist (both NAAT and WGS based 79 ), with the WHO now pushing for better access to rapid testing 80 . The UK is leading on that front, having implemented the first service for TB rapid diagnostics utilising WGS, shortening TB diagnosis and treatment in a cost-effective way 81 . This successful implementation is a promising first step for a wider adoption of rapid diagnostics in healthcare for other indications.
Conditions affecting the skin can be both physically painful and disfiguring, leading to both physical discomfort, mental distress and social isolation. Among medical practitioners, dermatologists have the highest prescription rates for antibiotics 82 . Nosocomial (healthcare-associated) infections are a serious complication of severe burns, and the use of systemic prophylactic antibiotics to control infections and reduce sepsis risk has been discussed in several studies over the past several years 83 . These studies have shown that prophylactic use of broad-spectrum antibiotics does not provide protection against sepsis, except for patients with inhalation burns or pneumonia. The overarching theme here is that broad spectrum antibiotics are often used for skin conditions, with little diagnostic or susceptibility screening performed. This needs to change to prevent further AMR evolution. Targeted therapy based on identification of the causative agent and its susceptibility will need to increase in importance.
Bacterial infections are common in patients with chronic liver disease (CLD) and are one of the most important causes of liver-related complications, progression to liver failure, and mortality in these patients 84 . Resorting to antibiotic prophylaxis and broad-spectrum empirical therapy remains essential in the management of infection prevention in advanced CLD 85 . This approach has however led to the widespread use of antimicrobials, which is the leading cause of the continuous rise of MDRO infections. MDRO rates to quinolone drugs have been recorded up to 40% in CLD patients with spontaneous bacterial peritonitis on prophylactic antibiotics, leading to a break-through recurrence of intra-peritoneal infection. MDR bacteria have emerged as a significant challenge in many countries 86 , and infections caused by these bacteria are associated with a particularly poor prognosis in CLD patients 87 .
Circumventing the harmful impact of AMR in CLD requires a combinatorial approach encompassing antibiotic stewardship programmes, accurate biomarkers of infection onset and resolution, prompting the rapid de-escalation of antimicrobial therapies 88 , 89 . The other crucial aspect remains the development of rapid testing technologies for the accurate identification of causative pathogens with simultaneous AMR profiling to guide timely and accurate antibacterial therapy in cirrhosis patients 90 This has paved the way for non-culture-based approaches that offer the potential in reducing the limitations, delays and inaccuracies that are associated with conventional microbiological techniques 91 .
Microbiome therapies are a growing area in medicine, offering novel approaches to disease management in instances of unmet clinical need or poor treatment outcomes 92 . Faecal microbiota transplant (FMT) is the first commercially available microbiome treatment, employed to treat recurrent Clostridioides difficile infections 93 . In 2019, the first death caused by FMT occurred in the USA when an immunocompromised adult received a FMT that led to an invasive infection caused by extended-spectrum beta-lactamase (ESBL)-producing E. coli present in the donor stool 94 . This triggered the FDA to recommend screening for common MDROs 95 in all donor samples, with the British Society of Gastroenterology and Healthcare Infection Society adopting similar recommendations 96 , 97 . Even with all these guidelines and safety measures now in place, cases of Shiga toxin E. coli infections caused by FMT are still occurring 98 , 99 , raising concern that pre-treatment screening is not sufficiently robust. Culture based testing for many bacteria may not be consistent or reliable 100 , 101 . In the case of FMT, false negatives become an unacceptable risk, with the danger of transmitting an infectious organism that was not detected during donor screening.
Molecular methods should be adopted for FMT screening (both for identification of pathogens and AMR assessment) since the sensitivity of this method is much higher than culture. WGS could add further value as it not only identifies strains in a complex mixture and screens for markers of AMR, but it can also provide data that could be used to identify microbiome dysbiosis, potentially before a disease has manifested. Other treatments using microbiome transplants (e.g., vaginal microbiome transplants for bacterial vaginosis) would also benefit from the availability of WGS screening and characterisation (strain ID and AMR).
The need for standards in antibiotic resistance gene detection by WGS is crucial in combating the global threat of antimicrobial resistance. WGS has emerged as a powerful tool for identifying and characterising antibiotic resistance genes in bacterial genomes. However, the lack of standardised protocols and guidelines for WGS-based resistance profile detection is hindering the accurate and consistent interpretation of results. Biological standardisation is necessary to ensure that different laboratories and researchers are harmonised in quality control measures and data analysis pipelines 102 , 103 . This will enable reliable comparisons of resistance profiles across studies and facilitate the development of robust surveillance systems. Furthermore, standardised protocols and the use of appropriate reference reagents will promote data sharing and collaboration, allowing for the accumulation of comprehensive and representative datasets that can inform evidence-based policies and interventions. Ultimately, the establishment of written and physical standards in antibiotic resistance gene detection by WGS will enhance our understanding of the global antimicrobial resistance landscape and support efforts to mitigate its impact on public health.
The rise of multi-drug resistant organisms (MDROs) poses a significant threat to global health, leading to increased mortality rates, healthcare and societal costs which necessitate radical intervention. Current methods for AMR detection, most significantly culture-based approaches, have limitations in terms of sensitivity, turnaround time, and the ability to detect all potential resistance genes. WGS offers a promising alternative, providing rapid and comprehensive information about the presence of AMR genes in bacterial strains (Fig. 1 ). However, several challenges need to be addressed before WGS can be widely implemented in clinical settings. These include the need for standardised methodologies, a comprehensive and unified database of known resistance genes, the availability of appropriate physical reference materials to assure assay performance and the establishment of clinical breakpoints for genomic predictions. Additionally, the cost of sequencing and the interpretation of sequencing results need to be considered to ensure LMICs can also access and derive maximal benefit, as well as optimising upstream processes including biological sample handling and DNA extraction. Despite these challenges, the potential benefits of WGS in AMR surveillance and evidence-based antimicrobial prescription are significant. Establishing standards for WGS-based AMR detection will help address these challenges and accelerate the adoption of this powerful tool in the fight against AMR, ultimately leading to more effective and targeted treatment strategies.
Current approach for infection diagnostics vs a WGS approach that supports AMR stewardship.
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Vishal C. Patel
Institute of Liver Studies, School of Immunology and Microbial Sciences, Faculty of Life Sciences and Medicine, King’s College London, 125 Coldharbour Lane, London, SE5 9NU, UK
Institute of Liver Studies, King’s College Hospital NHS Foundation Trust, Denmark Hill, London, SE5 9RS, UK
Centre for Clinical Infection and Diagnostics Research, Guy’s and St Thomas’ NHS Foundation Trust and King’s College, London, UK
Simon D. Goldenberg
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Hassall, J., Coxon, C., Patel, V.C. et al. Limitations of current techniques in clinical antimicrobial resistance diagnosis: examples and future prospects. npj Antimicrob Resist 2 , 16 (2024). https://doi.org/10.1038/s44259-024-00033-8
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Home > Conferences > AMCIS > AMCIS 2024 Proceedings > IS in Educ, IS Curriculum, and Teaching Cases (SIG ED) > 12
Proposal - Security Certifications, Degrees, & Work Experience: Which is better?
Garry White , Texas State Univeristy Follow
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There’s a widespread understanding that managing corporate culture is key to business success. Yet few companies articulate their culture in such a way that the words become an organizational reality that molds employee behavior as intended.
All too often a culture is described as a set of anodyne norms, principles, or values, which do not offer decision-makers guidance on how to make difficult choices when faced with conflicting but equally defensible courses of action.
The trick to making a desired culture come alive is to debate and articulate it using dilemmas. If you identify the tough dilemmas your employees routinely face and clearly state how they should be resolved—“In this company, when we come across this dilemma, we turn left”—then your desired culture will take root and influence the behavior of the team.
To develop a culture that works, follow six rules: Ground your culture in the dilemmas you are likely to confront, dilemma-test your values, communicate your values in colorful terms, hire people who fit, let culture drive strategy, and know when to pull back from a value statement.
Start by thinking about the dilemmas your people will face.
The problem.
There’s a widespread understanding that managing corporate culture is key to business success. Yet few companies articulate their corporate culture in such a way that the words become an organizational reality that molds employee behavior as intended.
How to fix it.
Follow six rules: Ground your culture in the dilemmas you are likely to confront, dilemma-test your values, communicate your values in colorful terms, hire people who fit, let culture drive strategy, and know when to pull back from a value.
At the beginning of my career, I worked for the health-care-software specialist HBOC. One day, a woman from human resources came into the cafeteria with a roll of tape and began sticking posters on the walls. They proclaimed in royal blue the company’s values: “Transparency, Respect, Integrity, Honesty.” The next day we received wallet-sized plastic cards with the same words and were asked to memorize them so that we could incorporate them into our actions. The following year, when management was indicted on 17 counts of conspiracy and fraud, we learned what the company’s values really were.
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Modeling and research on offshore casing cutting of hydraulic internal cutting device.
2. mechanical casing cutting device, 2.1. basic structure of mechanical casing cutting device, 2.2. working principle, 3. the theory model of casing cutting, 3.1. the relationship between piston displacement and cutting tool tip radius, 3.2. calculation of cutting torque, 3.3. calculation of wellhead driving torque, 4. the 2d cutting simulation based on abaqus, 4.1. theoretical model of cutting, 4.2. simulation model and boundary conditions based on abaqus, 4.3. simulation analysis and results based on abaqus, 4.3.1. the influence of different tool rotational speeds on cutting simulation, 4.3.2. the impact of different cutting depths on cutting simulation, 4.3.3. the impact of different tool front angles on cutting simulation, 4.3.4. summary of the chapter, 5. analysis of influencing factors on the cutting efficiency of the cutting tool, 5.1. the cutter face angle α, 5.2. the driving force of drilling fluid f 0, 5.3. the cutting depth l and revolution of drill string n, 6. case study and discussion, 6.1. field casing cutting operation condition, 6.2. torque comparison at different rotational speeds, 7. conclusions, author contributions, informed consent statement, data availability statement, conflicts of interest.
Click here to enlarge figure
A/MPa | B/MPa | C | n | m |
---|---|---|---|---|
1150 | 739 | 0.014 | 0.26 | 1.03 |
Parameters | Value | Parameters | Value |
---|---|---|---|
/mm | 151 | f | 3.5 |
/mm | 168 | 32 | |
qm/(Kg/m) | 122 | n/(r/min) | 45 |
K | 3 | /( ) | 85 |
ρ/(kg/m ) | 1025 | L/m | 850 |
g/(N/Kg) | 9.8 | 313 | |
Sz/mm | 0.12 | 340 | |
Z | 12 | 298 |
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Sun, Q.; Tian, J.; Jin, Y.; Feng, D.; Hou, L. Modeling and Research on Offshore Casing Cutting of Hydraulic Internal Cutting Device. J. Mar. Sci. Eng. 2024 , 12 , 1026. https://doi.org/10.3390/jmse12061026
Sun Q, Tian J, Jin Y, Feng D, Hou L. Modeling and Research on Offshore Casing Cutting of Hydraulic Internal Cutting Device. Journal of Marine Science and Engineering . 2024; 12(6):1026. https://doi.org/10.3390/jmse12061026
Sun, Qiaolei, Jie Tian, Yujie Jin, Ding Feng, and Lingxia Hou. 2024. "Modeling and Research on Offshore Casing Cutting of Hydraulic Internal Cutting Device" Journal of Marine Science and Engineering 12, no. 6: 1026. https://doi.org/10.3390/jmse12061026
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IMAGES
VIDEO
COMMENTS
Common types of limitations and their ramifications include: Theoretical: limits the scope, depth, or applicability of a study. Methodological: limits the quality, quantity, or diversity of the data. Empirical: limits the representativeness, validity, or reliability of the data. Analytical: limits the accuracy, completeness, or significance of ...
In research, studies can have limitations such as limited scope, researcher subjectivity, and lack of available research tools. Acknowledging the limitations of your study should be seen as a strength. It demonstrates your willingness for transparency, humility, and submission to the scientific method and can bolster the integrity of the study.
Limitation #3: Sample Size & Composition. As we've discussed before, the size and representativeness of your sample are crucial, especially in quantitative research where the robustness of your conclusions often depends on these factors.All too often though, students run into issues achieving a sufficient sample size and composition. To ensure adequacy in terms of your sample size, it's ...
Some Examples of Limitations in Research are as follows: Example 1: Research Title: ... Generally, limitations should be discussed in the conclusion section of a research paper or thesis, although they may also be mentioned in other sections, such as the introduction or methods. The specific limitations that are discussed will depend on the ...
how the study enables future research—will help ensure that the study's drawbacks are not the last thing reviewers read in the paper. Start this "limitations" paragraph with a simple topic sentence that signals what you're about to discuss. For example: "Our study had some limitations."
Sample Size Limitations in Qualitative Research. Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework.
Step 1. Identify the limitation (s) of the study. This part should comprise around 10%-20% of your discussion of study limitations. The first step is to identify the particular limitation (s) that affected your study. There are many possible limitations of research that can affect your study, but you don't need to write a long review of all ...
Here's an example of a limitation explained in a research paper about the different options and emerging solutions for delaying memory decline. These statements appeared in the first two sentences of the discussion section: "Approaches like stem cell transplantation and vaccination in AD [Alzheimer's disease] work on a cellular or molecular level in the laboratory.
The ideal way is to divide your limitations section into three steps: 1. Identify the research constraints; 2. Describe in great detail how they affect your research; 3. Mention the opportunity for future investigations and give possibilities. By following this method while addressing the constraints of your research, you will be able to ...
3. Identify your limitations of research and explain their importance. 4. Provide the necessary depth, explain their nature, and justify your study choices. 5. Write how you are suggesting that it is possible to overcome them in the future. Limitations can help structure the research study better.
Limitations of a dissertation are potential weaknesses in your study that are mostly out of your control, given limited funding, choice of research design, statistical model constraints, or other factors. In addition, a limitation is a restriction on your study that cannot be reasonably dismissed and can affect your design and results.
For example, in their 2021 Cell Reports study on macrophage polarization mechanisms, dermatologist Alexander Marneros and colleagues wrote the following. 1. A limitation of studying macrophage polarization in vitro is that this approach only partially captures the tissue microenvironment context in which many different factors affect macrophage polarization.
2.3. Limitations Example 3. It is important to remember not to end your paper with limitations. Finish your paper on a positive note by telling your readers about the benefits of your research and possible future directions. In the following example, right after listing the limitations, the authors proceed to talk about the positive aspects of ...
Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study.
Limitations are usually listed at the end of your Discussion section, though they can also be added throughout. Especially for a long manuscript or for an essay or dissertation, the latter may be useful for the reader. Writing on your limitations: Words and structure. This study did have some limitations. Three notable limitations affected this ...
Possible Methodological Limitations. Sample size-- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample ...
Research Limitations. Research limitations are, at the simplest level, the weaknesses of the study, based on factors that are often outside of your control as the researcher. These factors could include things like time, access to funding, equipment, data or participants.For example, if you weren't able to access a random sample of participants for your study and had to adopt a convenience ...
Well, that depends entirely on the nature of your study. You'll need to comb through your research approach, methodology, testing processes, and expected results to identify the type of limitations your study may be exposed to. It's worth noting that this understanding can only offer a broad idea of the possible restrictions you'll face ...
For example, if conducting a meta-analysis of the secondary data has not been stated as your research objective, no need to mention it as your research limitation. Research limitations in a typical dissertation may relate to the following points: 1. Formulation of research aims and objectives. You might have formulated research aims and ...
There is no "one best way" to structure the Research Limitations section of your dissertation. However, we recommend a structure based on three moves: the announcing, reflecting and forward looking move. The announcing move immediately allows you to identify the limitations of your dissertation and explain how important each of these ...
Writing the limitations of the research papers is often assumed to require lots of effort. However, identifying the limitations of the study can help structure the research better. Therefore, do not underestimate the importance of research study limitations. 3. Opportunity to make suggestions for further research.
conference, or a published research paper in an academic journal. "Limitations of Research". is a section in the standard research report (the research report is usually divided into the ...
Any limitation influences a research paper. It is unknown how much and to what extent any limitation affects other limitations, but it does create a cascading domino effect of ever-increasing interactions that compromise findings and conclusions. ... This is a sample of limitations and a few of their component variables under the rubric of a ...
Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion. Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and ...
The term 'lived experience' has its origins in phenomenology, though historically it has been focussed on participants as the 'subject' of research rather than as active contributors throughout the research process (Frechette et al., 2020).Lived experience researchers or co-researchers are defined, for the purposes of this paper, as people who carry out research with knowledge and ...
The sample covers research published in 56 journals. ... Most of these papers suggest hybrid mentoring is positively related to the full range of career development outcomes, ... as well as general sample size limitations, prevented this analysis. Nonetheless, where possible (e.g. mentoring for targeted groups) the review does provide nuanced ...
Antimicrobial resistance is a global threat to public health. Without proactive intervention, common infections may become untreatable, restricting the types of clinical intervention that can be ...
Please note several limitations on length: (1) your abstract should be no more than 150 words, as the abstract will also be used for the conference program, (2) your completed research paper should be no more than 10 pages (approx. 5,000 words, including figures, tables, references, and appendices).
At the beginning of my career, I worked for the health-care-software specialist HBOC. One day, a woman from human resources came into the cafeteria with a roll of tape and began sticking posters ...
The field example shows the limitation of judging casing cutting by a sudden drop in torque. ... Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future ...