( = 10) .
Characteristic . | Total ( = 30) . | Low Engagement ( = 10) . | Medium Engagement ( = 10) . | High Engagement ( = 10) . |
---|---|---|---|---|
Female sex | 14 (47) | 5 (50) | 3 (30) | 6 (60) |
Geographic region | ||||
Ontario | 13 (43) | 5 (50) | 5 (50) | 3 (30) |
Quebec | 8 (27) | 3 (30) | 1 (10) | 4 (40) |
Western Provinces | 7 (23) | 2 (20) | 2 (20) | 3 (30) |
Atlantic Provinces | 2 (7) | 0 (0) | 2 (20) | 0 (0) |
Years since type 2 diabetes diagnosis, mean ± SD (range) | 12.9 ± 7.9 (1–30) | 9.2 ± 7.2 (1–22) | 11.3 ± 7.4 (2–21) | 18.1 ± 6.9 (5–30) |
Takes more than one diabetes medication | 15 (50) | 4 (40) | 5 (50) | 6 (60) |
Medications | ||||
Metformin only | 9 (30) | 4 (40) | 3 (30) | 2 (20) |
Oral medication(s) other than or in addition to metformin | 9 (30) | 3 (30) | 3 (30) | 3 (30) |
Insulin with or without metformin or other oral medication(s) | 3 (10) | 0 (0) | 2 (20) | 1 (10) |
Noninsulin injectable with or without metformin or other oral medication(s) or insulin | 9 (30) | 3 (30) | 2 (20) | 4 (40) |
Data are n (%) except where noted.
Forty-two themes were identified and mapped to 12 of the 14 theme domains, with the knowledge and skills domains being the exceptions. The most prominent domains, as determined by high-frequency themes or themes for which people with low and high medication-taking had contrasting perspectives were emotion (2 themes); memory, attention, and decision processes (6 themes); behavioral regulation (5 themes); beliefs about consequences (8 themes); goals (3 themes); and environmental context and resources (4 themes). The key themes from the most prominent domains are discussed below, along with illustrative quotes captured during the interviews. A list of all of the identified themes is provided in Supplementary Table S1 .
“Because I take so many medications—at times, I just get frustrated with it—that I’m so ill all the time and I get an attitude like, ‘Oh, well. Who cares? I’m going to do what I want, eat what I want. Sort of like a lack of total awareness of what happens when I don’t take the medicine. I’m just in a mood that I don’t care . . . . I am very tired of taking loads of pills every day after many years.” (low engagement)
“The fact that I have to take it at all—no, doesn’t make me feel good at all—makes me feel like a total failure. Diabetes was pretty much my own fault because of the huge weight gain I had when I was a kid. . . . but it’s my own fault.” (low engagement)
“For me, it is about accountability and being more responsible in my day-to-day life for how I’m feeling and how I’m doing. Medication is a huge part of that. Being responsible and organized and taking the medication is definitely a part of who I am now. It’s a normal, everyday occurrence, but it’s something I have to do.” (high engagement)
“I would typically travel every 6 months . . . and, absolutely, sometimes I will forget to take the medication with me. Or, just because you’re traveling—you’re outside with family and friends—you’re not able to stick to your regimen. You forget it.” (low engagement)
“All of my medications are very stable and portable, so whenever I have traveled, it’s easy to take everything with me.” (high engagement)
“If work is too busy, I tend to skip one of my doses. Usually there will be social events with friends or long trips or a busy work schedule—they are the activities that interfere with my medication . . . . I skip the doses.” (low engagement)
“I babysit my granddaughter, and she takes up a lot of my time. I forget for a while, but I always take it after.” (high engagement)
“The most important is eating healthy because even if you don’t exercise and you don’t take your medication, if you’re eating healthy, you’re still going to be able to control your sugar levels.” (low engagement)
“Sometimes, I just wake up the next day and go, ‘Oh, I didn’t take the meds last night, did I?’” (low engagement)
“I made everything habit. Once it’s habit, it becomes automatic—you just do it.” (medium engagement)
“I take it in the morning and in the evening—it’s routine. I do go to bed every evening, so I know that I have to take my medication. And in the morning, when I wake up, I take the other medications.” (high engagement)
“I could set alarms on my phone, but I don’t. I don’t use anything, no.” (low engagement)
“[I have] notifications on the phone, blister packs, and . . . Post-It notes and having my family around me, who ask, ‘Did you remember to take this? Did you remember to do that?’” (high engagement)
“Meeting with friends, or any kind of social events, or if I go on long trips—these are activities that are interfering with my medications.” (low engagement)
“It’s a timing thing. It [medication] causes gurgling and gas and all kinds of nastiness, so if I’m going to a restaurant, I would’ve thought ‘I’m going to wait until I’m done with the restaurant to take the pill’ . . . steering around my schedule a little bit. I try not to miss, but if I miss, I wait until the next time. I don’t double dose.” (low engagement)
“In the morning, if my routine is broken, sometimes I can forget, but it’s rare. Almost like a step-by-step thing in the morning. So, I do A, B, C . . . D is taking the pills.” (high engagement)
“Medications come with their own side effects, and they ruin other things, like your liver and kidney and whatever.” (low engagement)
“I was told by the doctor to take [my medication] 3 times a day. At first, I really wanted to follow those instructions from the doctor, but then I would get side effects, like I would have diarrhea and metallic taste . . .. It’s not practical. It’s very uncomfortable . . . . I would only take the medicine if I’m staying at home . . . but if I’m working or doing errands outside . . . I stop taking it.” (low engagement)
“I wish there was just one magic pill or one magic injection that will take care of all of it.” (low engagement)
“This medication is helping me. I’m not going to stop taking it. I’m a much happier person. I’m a much better person to my family and everyone as long as I take my medication.” (high engagement)
“The cost is getting to be huge for diabetics. Right now, when you haven’t been working for a year . . . someone on a fixed income . . . and it’s been going up in price—let’s say an average of $170–180 every 2 months for your supplies. And that’s not including your test strips. That is a lot of money.” (medium engagement)
“Initially, I was scared of the drug because I have read [online] that metformin usually causes Alzheimer’s, but later on, when I kept searching, I said, ‘Okay, it’s safe.’ But still, I’m having my concerns about how metformin side effects are going to be in the long term. I was concerned taking it long term.” (low engagement)
Through qualitative interviews, we identified themes and barriers affecting medication-taking among people with type 2 diabetes in Canada using the TDF, with six prominent theme domains identified. These domains were 1 ) emotion; 2 ) memory, attention, and decision processes; 3 ) behavioral regulation; 4 ) beliefs about consequences; 5 ) goals; and 6 ) environmental context and resources. To our knowledge, this is the first study to apply the TDF to qualitative one-on-one interviews with people with type 2 diabetes to provide a greater understanding of the situational context and drivers of medication-taking behavior.
The results from our study extend those of prior studies in several ways, providing further context for the ways in which complex dosing plans, tolerability of medications, and perceptions of risks and benefits of medications ( 13 ) contribute to engagement. These findings also present additional context for how both unintentional nonengagement behaviors, such as forgetfulness and beliefs about the need for medication, and intentional nonengagement behaviors contribute to taking medication as recommended ( 27 , 28 ).
Polonsky and Henry ( 4 ) emphasized that innovative strategies to improve the attitudes of people with type 2 diabetes toward medication or encourage habit formation regarding medication-taking may help increase engagement. Our study used the TDF to identify specific intentional and unintentional behavioral influences on medication nonengagement that were common among people with low medication-taking. This information was further enriched by contrasting the attitudes and behaviors of people with higher medication-taking to derive recommended areas of change. By leveraging findings from our approach, strategies to increase medication-taking can be tailored to target specific behavioral influences and contextual challenges.
Our results can be applied to the development and application of effective interventions to increase medication-taking, and these should take into account the broader TDF theme domains we identified, as well as target specific themes within each domain ( 29 ). For example, people with type 2 diabetes with low engagement experience emotional challenges associated with being overwhelmed by living with diabetes and needing to take medication. Therefore, diabetes self-management support interventions might benefit from incorporating emotion management strategies for people who struggle with diabetes and treatment acceptance ( Supplementary Table S1 , theme 13.1). Diabetes self-management education that provides concise and reliable diabetes and medication knowledge might mitigate issues associated with individuals’ past experiences of having unreliable information sources ( Supplementary Table S1 , theme 11.3) and also address feelings about medication-taking ( Supplementary Table S1 , theme 6.2). The individuals expressed a desire for information that is simple and easily accessible, supports setting expectations regarding side effects, and increases their understanding of the long-term benefits of treatment. Furthermore, we suggest that improving access to resources such as diabetes clinics, pharmacists, and support groups where people with type 2 diabetes can ask questions, receive coaching, and get essential education and training would be useful. These strategies would provide an opportunity to reframe negative feelings about diabetes and medications ( Supplementary Table S1 , theme 13.2). These approaches could also specifically target identified themes such as the importance of long-term goal setting ( Supplementary Table S1 , theme 9.3) and understanding the role of medications in type 2 diabetes treatment and the progressive nature of the disease (i.e., that it usually requires long-term medication use) ( Supplementary Table S1 , themes 9.2 and 10.3).
Likewise, practical support that facilitates medication-taking and increases accessibility may help to increase engagement. It was apparent in this study that disruptions to routines affected individuals who reported low engagement more than those with medium or high engagement, resulting in unintentionally or intentionally forgetting, skipping, or delaying medication doses ( Supplementary Table S1 , themes 10.1, 10.2, and 14.5). This finding highlights an important consideration when selecting medication plans, which should incorporate individuals’ convenience and lifestyle considerations to encourage engagement.
Our findings also highlight the importance of people with type 2 diabetes establishing a medication-taking routine. A number of participants reporting low engagement did not use reminders, whereas those with high engagement had a clear and defined process, including organization resources such as pill boxes and pharmacy-prepared personalized blister packs and tracking resources such as phone alarms, calendars, and diaries ( Supplementary Table S1 , theme 14.2). Thus, encouraging or enabling the use of such tools among people with type 2 diabetes may increase engagement, although success in using these tools may be more a result of individuals’ motivations and organizational skills rather than the mere availability of the tools.
There is also a role for pharmacist teams to identify people with or at risk for low engagement and to support these individuals through actions such as sending refill reminders, dispensing medication in personalized blister packs, and accommodating emergency medication needs, in addition to having conversations with and supporting people with type 2 diabetes in individualized appointments.
Finally, financial barriers such as high costs of medications and glucose monitoring supplies ( Supplementary Table S1 , theme 11.1) can be diminished through health system changes (specifically, covering diabetes-related care products and medications) and through support programs.
There are limitations to our study that should be considered for proper interpretation of the results. First, although quota sampling was conducted to ensure diversity among the participants, little diversity was reflected in recruited participants. Therefore, our participants may not have been representative of all people with type 2 diabetes in Canada. Second, social desirability bias, in which respondents tend to provide answers that overreport desirable and underreport less desirable attributes is a known concern with interviews. However, this problem was mitigated by our comprehensive discussion guide, which approached the topic of medication-taking from many perspectives, as well as by contrasting the responses of people with lower and higher medication-taking engagement. Third, although generating data using the TDF has been shown to be a comprehensive and inclusive approach to exploratory research, it is still a descriptive framework rather than a theory ( 30 ). The results generated do not specify relationships between the domains and do not generate testable hypotheses ( 31 ). Finally, we recognize that qualitative interviews about behavioral influences represent the perceptions of the individuals interviewed and may not reflect the actual causes of their behaviors or be generalizable to broader populations ( 30 ).
Our study identified behavioral influences contributing to lower medication-taking engagement, highlighting key areas for change among a small group of people with type 2 diabetes. Future research is warranted to validate these findings within a larger sample and to explore the suitability of various intervention and implementation options to improve medication-taking ( 32 ). Additionally, the results of this study can inform the development of medical education and training programs for health care providers supporting people with type 2 diabetes in Canada.
This article contains supplementary material online at https://doi.org/10.2337/figshare.25270123 .
The authors thank the people with type 2 diabetes who took part in qualitative interviews for this study. They also thank Carole Hamersky, PhD, and Cory Gamble, MD, of Novo Nordisk Canada, Inc., for expert advice on developing the qualitative discussion guide. The authors thank the following individuals from Real World Solutions, IQVIA Solutions Canada, Inc.: Andrean Bunko, MSc, and Pierre-François Meyer, PhD, for their support conducting interviews, coding, and reviewing theme domain mapping; Atif Kukaswadia, PhD, and Calum S. Neish, PhD, for their guidance and oversight throughout the project; and Vibha Dhamija, MSc, and Saurabh Trikha, PhD, for their assistance with medical writing.
This study was funded by Novo Nordisk Canada, Inc.
M.V., S.J., and N.M.I. received advisory fees from IQVIA Solutions Canada, Inc., for contributions to the design and interpretation of the study but received no compensation for development of the manuscript. A.K.-A. is an employee of Novo Nordisk Canada, Inc. G.N. is a consultant employed by IQVIA Solutions Canada, Inc., to support this study sponsored by Novo Nordisk Canada, Inc. No other potential conflicts of interest relevant to this article were reported.
All authors reviewed the TDF mapping results and participated in the interpretation of results, reviewed and revised the manuscript, and approved the final manuscript. G.N. conducted the interviews, coded the themes, and conducted the theme domain mapping. G.N. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Parts of this article were presented in abstract form at the American Diabetes Association’s 82nd Scientific Sessions, 3–7 June 2022.
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2023 Theses Doctoral
Rhodes-Bratton, Brennan
The disproportionate concentration of unhealthy food in communities of color in the United States may contribute to health inequities and food insecurity. Gentrification has been associated with residents’ increased adverse health outcomes in its early and rapid phases. This study adds to the growing body of research by examining the relationship between gentrification, the food environment, food habits (the interplay between food chances and food choices), and health in New York City. I used a mixed methods approach to assess the food landscape in NYC between 1990 and 2014, using group-based trajectory modeling, the National Establishments Time-Series database, census data, and in-depth interviews with mothers from the Columbia Center for Children’s Environmental Health study. I found that the growth in the food environment was unevenly distributed. While healthy food chances declined across all examined neighborhoods, unhealthy food chances quickly grew, commanding dominance. It was gentrifying neighborhoods; however, that surprisingly experienced the most remarkable growth in unhealthy food chances compared to other neighborhoods. A cross-tabulation of the food chance trajectories of New York City census tracts indicated the presence of food ecologies that exhibit both healthy and unhealthy food chances. There was a strong association between the type of food ecology and gentrification status (p < 0.001). The in-depth interviews corroborated these findings and revealed that food insecurity is a by-product of gentrification in two ways. First, neighborhoods in the early stages of gentrification are inundated with unhealthy food chances, such as fast-food chains, without adequate access to quality, fresh, healthy foods. Secondly, when healthy food chances finally arrive in resource-deprived areas through gentrification, families are forced to relocate to areas without access to fresh, affordable, healthy foods due to the increased cost of living. This cycle of food insecurity is inequitable due to historical racial segregation, exploitative capitalistic markets, and racist stereotypes. Speculators invest in unhealthy food chances aligned with pre-existing stereotypes, assumptions, and beliefs that such communities do not or will not consume healthier foods. Therefore, a cycle of structural racism reinvents itself through this investment in unhealthy food chances, constructing food deserts and swamps bestowed upon communities experiencing poverty and disproportionate adverse cardiovascular health conditions. Strengthening policy focused on the relationship between gentrification mitigation and health outcomes is needed.
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Introduction Children with monogenic neurodevelopmental disorders often grow abnormally. Gene-specific growth charts would be useful but require large samples to construct them using the conventional LMS method.
Methods We transformed anthropometry to British 1990 reference z-scores for 328 UK and 264 international probands with ANKRD11, ARID1B, ASXL3, DDX3X, KMT2A or SATB2- related disorders, and modelled mean and standard deviation (SD) of the z-scores as gene-specific linear age trends adjusted for sex. Back-transforming the mean ±2 SD lines provided gene-specific median, 2 nd and 98 th centiles.
Results The resulting z-score charts look plausible on several counts. Only KMT2A shows a (rising) age trend in median height, while BMI and weight increase in several genes, possibly reflecting population trends. Apart from SATB2 and DDX3X, the gene-specific medians are all below the reference (range 0.1 th centile for height KMT2A to 36 th centile for BMI ANKRD11 ). Median OFC shows no age trend, with medians ranging from 10 th -30 th centile, and ASXL3 lowest, on the 3 rd centile. There are no sex differences in 19/24 cases.
Conclusions Our LMSz method produces gene-specific growth charts for rare diseases, an essential clinical tool for paediatric care. We plan to automate it within the DECIPHER platform, enabling availability for all relevant genes.
The authors have declared no competing interest.
Funding statement The DDD study presents independent research commissioned by the Health Innovation Challenge Fund [grant number HICF-1009-003], a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Sanger Institute [grant number WT098051]. This study was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network. JF is funded by the Wellcome Trust [grant number WT223718/Z/21/Z]. This research was funded in whole or in part by the Wellcome Trust. MB is funded by the MRC (MR/V037307/1). For the purpose of open access, the author has applied a CC-BY public copyright licence to any author accepted manuscript version arising from this submission. KL is supported by the National Institute for Health and Care Research Doctoral Research Fellowship 302303. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
The DDD study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South REC, and GEN/284/12 granted by the Republic of Ireland REC). All participants gave informed consent, as required by the REC. All published data were de-identified. Specific ethical approval for the growth charts development was given via a DDD Complementary Analysis Proposal Approval (CAP#371). The GenROC study received East Midlands - Nottingham Research Ethics Committee (REC) approval on 15 December 2022 and Health Research Authority approval on 9 February 2023. The ASXL3 Natural History Study, sponsored by Sheffield Children's Hospital and The University of Sheffield (UK) received REC (23/SC/0151) and HRA approval on 2 June 2023. All participants enrolled in the study gave informed consent for anonymised data sharing to allow this collaboration.
I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.
Sequence and variant-level data and phenotypic data for the DDD study data are available from the European Genome-phenome Archive (EGA; https://www.ebi.ac.uk/ega/ ) with study ID EGAS00001000775. Clinically interpreted variants and associated phenotypes from the DDD study and GenROC study are available through DECIPHER ( https://www.deciphergenomics.org/ ).
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In awake mice, researchers found that even low stimulation currents could sometimes still cause electrographic seizures
The idea of electrically stimulating a brain region called the central thalamus has gained traction among researchers and clinicians because it can help arouse subjects from unconscious states induced by traumatic brain injury or anesthesia, and can boost cognition and performance in awake animals. But the method, called CT-DBS, can have a side effect: seizures. A new study by researchers at MIT and Massachusetts General Hospital (MGH) who were testing the method in awake mice, quantifies the probability of seizures at different stimulation currents and cautions that they sometimes occurred even at low levels.
“Understanding production and prevalence of this type of seizure activity is important because brain stimulation-based therapies are becoming more widely used,” said co-senior author Emery N. Brown, Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience in The Picower Institute for Learning and Memory, the Institute for Medical Engineering and Science, the Department of Brain and Cognitive Sciences and the Center for Brains Minds and Machines (CBMM) at MIT.
In the brain, the seizures associated with CT-DBS occur as “electrographic seizures” which are bursts of voltage among neurons across a broad spectrum of frequencies. Behaviorally, they manifest as “absence seizures” in which the subject appears to take on a blank stare and freezes for about 10-20 seconds.
In their study, the researchers were hoping to determine a CT-DBS stimulation current— in a clinically relevant range of under 200 microamps—below which seizures could be reliably avoided.
In search of that ideal current, they developed a protocol of starting brief bouts of CT-DBS at 1 microamp and then incrementally ramping the current up to 200 microamps until they found a threshold where an electrographic seizure occurred. Once they found that threshold, then they tested a longer bout of stimulation at the next lowest current level in hopes that an electrographic seizure wouldn’t occur. They did this for a variety of different stimulation frequencies. To their surprise, electrographic seizures still occurred 2.2 percent of the time during those longer stimulation trials (i.e. 22 times out of 996 tests) and in 10 out of 12 mice. At just 20 microamps, mice still experienced seizures in 3 out of 244 tests, a 1.2 percent rate.
“This is something that we needed to report because this was really surprising,” said co-lead author Francisco Flores, a research affiliate in The Picower Institute and CBMM, and an instructor in anesthesiology at MGH where Brown is also an anesthesiologist. Isabella Dalla Betta, a technical associate in The Picower Institute, co-led the study published in Brain Stimulation .
Stimulation frequency didn’t matter for seizure risk but the rate of electrographic seizures increased as the current level increased. For instance, it happened in 5 out of 190 tests at 50 microamps, and 2 out of 65 tests at 100 microamps. The researchers also found that when an electrographic seizure occurred, it did so more quickly at higher currents than at lower levels. Finally, they also saw that seizures happened more quickly if they stimulated the thalamus on both sides of the brain vs. just one side. Some mice exhibited behaviors similar to absence seizure, though others became hyperactive.
It is not clear why some mice experienced electrographic seizures at just 20 microamps while two mice did not experience the seizures even at 200. Flores speculated that there may be different brain states that change the predisposition to seizures amid stimulation of the thalamus. Notably, seizures are not typically observed in humans who receive CT-DBS while in a minimally conscious state after a traumatic brain injury or in animals who are under anesthesia. Flores said the next stage of the research would aim to discern what the relevant brain states may be.
In the meantime, the study authors wrote, “EEG should be closely monitored for electrographic seizures when performing CT-DBS, especially in awake subjects.”
The paper’s co-senior author is Matt Wilson, Sherman Fairchild Professor in The Picower Institute, CBMM, and the departments of Biology and Brain and Cognitive Sciences. In addition to Dalla Betta, Flores, Brown and Wilson, the study’s other authors are John Tauber, David Schreier, and Emily Stephen.
Support for the research came from The JPB Foundation, The Picower Institute for Learning and Memory, George J. Elbaum (MIT ‘59, SM ‘63, PhD ‘67), Mimi Jensen, Diane B. Greene (MIT, SM ‘78), Mendel Rosenblum, Bill Swanson, annual donors to the Anesthesia Initiative Fund; and the National Institutes of Health.
Method enables fast, accurate estimates of cardiovascular state to inform blood pressure management.
COMMENTS
Case Study Research Methodology. This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group. Action Research Methodology
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What is research methodology? Research methodology simply refers to the practical "how" of a research study. More specifically, it's about how a researcher systematically designs a study to ensure valid and reliable results that address the research aims, objectives and research questions. Specifically, how the researcher went about deciding:
Definition, Types, and Examples. Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of ...
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:
Research methodology is the backbone of any successful study, providing a structured approach to collecting and analysing data. It encompasses a broad spectrum of methods, each with specific processes and applications, tailored to answer distinct research questions.
Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings.
The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study's overall validity and reliability.
A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more. You can think of your research methodology as being a formula. One part will be how you plan on putting your research into ...
Research methodology is the process or the way you intend to execute your study. The methodology section of a research paper outlines how you plan to conduct your study. It covers various steps such as collecting data, statistical analysis, observing participants, and other procedures involved in the research process
In this tutorial paper, we will use the term methodological study to refer to any study that reports on the design, conduct, analysis or reporting of primary or secondary research-related reports (such as trial registry entries and conference abstracts). In the past 10 years, there has been an increase in the use of terms related to ...
The research design is a fundamental aspect of research methodology, outlining the overall strategy and structure of the study. It includes decisions regarding the research type (e.g., descriptive, experimental), the selection of variables, and the determination of the study's scope and timeframe. We must carefully consider the design to ...
In many ways, learning research methods is learning how to see and make these decisions." The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more. This guide is an introduction, but if you don't see what you need here, always contact your ...
2.1 Research Methodology. Method can be described as a set of tools and techniques for finding something out, or for reducing levels of uncertainty. According to Saunders (2012) method is the technique and procedures used to obtain and analyse research data, including for example questionnaires, observation, interviews, and statistical and non-statistical techniques [].
1. Understanding the options. Before we jump into the question of how to choose a research methodology, it's useful to take a step back to understand the three overarching types of research - qualitative, quantitative and mixed methods -based research. Each of these options takes a different methodological approach.
Understanding different research methods: There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based. Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research ...
Background Methodological studies - studies that evaluate the design, analysis or reporting of other research-related reports - play an important role in health research. They help to highlight issues in the conduct of research with the aim of improving health research methodology, and ultimately reducing research waste. Main body We provide an overview of some of the key aspects of ...
A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.
components of methodology one could add. For example, the historical roots of science and science and social policy are legitimate topics that could be covered as well. Yet, in developing an appreciation for methodology and the skills involved in many of the key facets of actually conducting research, the five will suffice.
A research methodology gives research legitimacy and provides scientifically sound findings. It also provides a detailed plan that helps to keep researchers on track, making the process smooth, effective and manageable. A researcher's methodology allows the reader to understand the approach and methods used to reach conclusions.
A research methodology is different from a research method because research methods are the tools you use to gather your data (Dawson, 2019). You must consider several issues when it comes to selecting the most appropriate methodology for your topic. ... Feminist research: The goal of this methodology is to study topics that have been dominated ...
Research can be defined as "an activity that involves finding out, in a more or less systematic way, things you did not know" (Walliman and Walliman, 2011, p.7). "Methodology is the philosophical framework within which the research is conducted or the foundation upon which the research is based" (Brown, 2006).
There are two ways to conduct research observations: Direct Observation: The researcher observes a participant in an environment. The researcher often takes notes or uses technology to gather data, such as a voice recorder or video camera. The researcher does not interact or interfere with the participants.
The scientific method is an empirical method for acquiring knowledge that has characterized the development of science since at least the 17th century. The scientific method involves careful observation coupled with rigorous scepticism, because cognitive assumptions can distort the interpretation of the observation.Scientific inquiry includes creating a hypothesis through inductive reasoning ...
Research Design: The overall plan of the research, determining the type of study, sample selection, data collection, and analysis methods. It ensures the research problem is addressed effectively.
Our study identified behavioral influences contributing to lower medication-taking engagement, highlighting key areas for change among a small group of people with type 2 diabetes. Future research is warranted to validate these findings within a larger sample and to explore the suitability of various intervention and implementation options to ...
The disproportionate concentration of unhealthy food in communities of color in the United States may contribute to health inequities and food insecurity. Gentrification has been associated with residents' increased adverse health outcomes in its early and rapid phases. This study adds to the growing body of research by examining the relationship between gentrification, the food environment ...
The GenROC study received East Midlands - Nottingham Research Ethics Committee (REC) approval on 15 December 2022 and Health Research Authority approval on 9 February 2023. The ASXL3 Natural History Study, sponsored by Sheffield Children's Hospital and The University of Sheffield (UK) received REC (23/SC/0151) and HRA approval on 2 June 2023.
Background: Shared decision-making is a patient-centered and a recovery-oriented mental health system in which consumers are encouraged to actively engage in illness management. Although shared decision-making research in mental health has evolved rapidly in the past two decades, there is a lack of studies examining the level and factors associated with shared decision-making practice in low ...
But the method, called CT-DBS, can have a side effect: seizures. A new study by researchers at MIT and Massachusetts General Hospital (MGH) who were testing the method in awake mice, quantifies the probability of seizures at different stimulation currents and cautions that they sometimes occurred even at low levels.