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In this blog post, we provide a comprehensive guide on planning and conducting a Diary Study research project. We cover the purpose of diary studies, explain how to set research objectives, recruit and incentivise participants, design effective tasks, and analyse the collected data #Indeemo #DiaryStudies #QualResearch #ConsumerResearch https://lnkd.in/e_v3fAaY

"Understanding and Mitigating Bias in Research Studies" **Bias : Bias is a systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others. It can significantly affect the validity and reliability of research results. ☑️Types of Bias and How to Remove Them: 1. Selection Bias: - Definition: Occurs when the participants included in the study are not representative of the general population. ✅How to Remove: - Use random sampling techniques. - Ensure all eligible participants have an equal chance of being included. - Use stratified sampling to ensure various subgroups are proportionately represented. 2. Measurement Bias: - Definition: Occurs when there is a systematic error in the measurement of variables. ✅How to Remove: - Use standardized and validated measurement tools. - Calibrate instruments regularly. - Train researchers and data collectors thoroughly. 3. Response Bias: - Definition: Happens when participants respond inaccurately or falsely to questions. ✅How to Remove: - Ensure anonymity and confidentiality to encourage honest responses. - Use neutral language and avoid leading questions. - Implement a mix of question formats (open-ended and closed-ended). 4. Publication Bias: - Definition: Occurs when the results of studies influence the decision to publish them, typically favoring positive results. ✅- How to Remove: - Register clinical trials and research studies in public databases. - Encourage the publication of all results, including negative and inconclusive findings. - Advocate for journals to adopt open-access policies and preprint repositories. 5. Recall Bias: - Definition: Arises when participants do not remember past events accurately. ✅ How to Remove: - Use prospective study designs where possible. - Use objective records rather than relying on participants’ memories. - Conduct interviews or surveys shortly after the event of interest. 6. **Observer Bias: - Definition:Occurs when researchers’ expectations influence their observations or interpretations. ✅How to Remove: - Implement double-blind study designs where neither participants nor researchers know the treatment assignments. - Train observers thoroughly and use multiple observers. - Use standardized protocols for data collection and analysis. *☑️Conclusion Bias can undermine the credibility of research. By understanding different types of bias and implementing strategies to minimize them, researchers can enhance the validity and reliability of their studies. Stay vigilant, stay unbiased! #Research #Bias #ScientificIntegrity #DataQuality #ClinicalResearch #ResearchMethodology #LinkedInLearning

How does the utilization of case studies in qualitative research methodology facilitate comprehensive exploration and nuanced understanding of intricate phenomena?   The potential of case studies to offer in-depth, contextually rich, and comprehensive insights into intricate phenomena in their natural environments is what makes them crucial to qualitative research methodology. Case studies are useful in qualitative research for the following key reasons.   1) Through in-depth examination of a specific example or event, case studies enable scholars to gain a thorough grasp of its complexities, dynamics, and context. Researchers can find subtleties and complexity with this amount of investigation that would not be found with other methods of research. 2) Case studies provide an understanding of a phenomenon's larger context by examining it in its natural environment. Because it offers a framework for comprehending how different elements interact and impact the phenomena under inquiry, this contextual awareness is essential for interpreting and making meaning from the findings. 3) Case studies are a useful tool for accurately and realistically portraying the complexity and diversity of many occurrences. Case studies provide a detailed description of the phenomena under study by closely investigating real-life circumstances. This allows for a more realistic representation of reality and reflects the phenomenon's different character. 4) An array of data sources, such as observations, records, and interviews, are frequently used in case studies. The wide range of data sources available to researchers offers a multitude of viewpoints and evidence sources, hence augmenting the validity and dependability of the results. Case studies provide insights that can guide professional practice, policy creation, and decision-making by analysing real-world instances and scenarios. 5) The flexibility and adaptability of the case study technique enable researchers to customise their strategy to the particular research issue, setting, and goals. Because of this versatility, researchers may gather and analyse data using a range of strategies, which guarantees that the study is solid and appropriate for the setting in which it is conducted.   6) Case studies can aid in the development of theories by offering factual data and insights that can guide the creation or improvement of preexisting concepts. Researchers can find patterns, connections, and underlying mechanisms that support the development of theories in the relevant discipline by carefully examining pertinent domains. In summary, the case study method is essential to qualitative research since it offers comprehensive and contextually rich insights into intricate phenomena. Because of its focus on context, richness, and depth of data, it is an effective method for investigating and comprehending real-world events in their natural environments.  

The machines are coming! Or rather, they have already arrived. Artificial Intelligence (AI) is the topic of the moment, and it's hard to imagine a future, or even a present, without it. Yet, the more I delve into AI, the more questions I find myself asking. If you're anything like me, you've probably wondered, "What does AI mean for the work I do?" Well, I've decided to find out! As part of my Masters in Careers Guidance in Higher Education, I'm conducting research into how we, as Careers practitioners, can incorporate AI into our careers practice and delivery. I'm looking for Careers practitioners in Higher Education to participate in my study over the next few months. If you're interested in participating in my research and learning more about how AI might be able to enhance your work, please read the attached participant leaflet and complete the registration via the link provided. Please feel free to share this call for participants with your network. If you have any questions, please get in touch. https://lnkd.in/ettB4pmq Best Oby

𝐓𝐡𝐞 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐁𝐞𝐭𝐰𝐞𝐞𝐧 𝐌𝐢𝐱𝐞𝐝 𝐌𝐞𝐭𝐡𝐨𝐝 𝐚𝐧𝐝 𝐌𝐮𝐥𝐭𝐢-𝐌𝐞𝐭𝐡𝐨𝐝 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 Read till the end 👇🏿 A Mixed Method Research combines qualitative data with quantitative data to gain a comprehensive understanding of a research question. With this approach, you integrate findings from both qualitative data and quantitative data And use the different data to complement each other, to create a more holistic approach. E.g. In a study that aims to find out the effect of social media exposure on the education of teens, you may use surveys (quantitative) to gather data on usage volume and patterns And Interviews (qualitative) to understand individual experiences. Multi-method Research uses different research methods within the same research paradigm (either qualitative or quantitative). It does not mix qualitative and quantitative approaches in the same study. It strengthens the research conclusions by allowing findings from different methods to corroborate or challenge each other. E.g. If your focus is on qualitative research, you can use both interviews and focus groups to gather in-depth insights into the effect of social media exposure on the education of teens. Which research methodology are you using? Are you a PhD student? PhD SafeSpace is a support community for you throughout your journey. Our goal is to make your journey easier and provide you with helpful resources. Click the link in below to apply to join our community https://lnkd.in/d54e_yah

In the context of qualitative research, what are the similarities and distinctions between the grounded theory and case study methods? 1) Grounded theory and case studies are qualitative research methods that prioritise extensive research and comprehension of social dynamics. Explore the intricacy of real-life events in the context of their natural environments to present an in-depth perspective. Both use inductive reasoning, which allows themes, patterns, and insights to emerge in the data without being constrained by assumptions. To acquire extensive and unique data, grounded theory and case studies frequently employ an array of data-gathering techniques, including observations, interviews, and analysis of documentation. 2) Grounded theory emphasises the creation of new theories by concentrating on the ideas and explanations that are developed from the data at hand. The process of grounded theory is frequently dynamic and iterative, including the simultaneous gathering and interpretation of evidence. A case study may entail a longer-term, more thorough investigation of one case, or a smaller number of instances over a longer time frame. Moreover, instead of necessarily creating a new theory, case studies frequently seek to offer an in-depth examination and understanding of a specific case or phenomenon. 3) The main goal of grounded theory is theory construction, intending to create explanations that are both abstract and deeply ingrained in the specific context. It often uses theoretical sampling, in which participants are chosen based on developing concepts and theories discovered throughout the study process. On the other hand, case studies are primarily concerned with offering thorough explanations and context-specific insights into a given situation. Selecting participants or instances that offer the most insightful information usually depends on the use of convenience or purposeful sampling. 4) Systematic coding and ongoing comparison are key components of grounded theory, which help researchers find patterns and create theories. The goal of grounded theory is theoretical generalisation, whereby the ideas produced may be more broadly applicable to comparable situations. Case study analysis can take several forms, such as theme analysis, cross-case analysis, or a thorough investigation of the characteristics of a particular case. The focus of a case study is transferability, which enables readers to recognise the distinctive features of each case in point while applying the lessons learned to analogous circumstances.   In conclusion, case studies strive to provide a thorough knowledge of particular situations, whereas grounded theory aims to produce novel theories.

There are various problem formulation techniques that researchers can use when designing a study. These techniques help in identifying and defining the research problem, setting research objectives, and formulating research questions or hypotheses. Here are some commonly used problem formulation techniques: 1. Conducting a comprehensive literature review helps researchers identify existing gaps or limitations in previous studies, which can be used as the basis for formulating their research problem (Webster & Watson, 2002). 2. Brainstorming wherein a group of experts or stakeholders generate ideas and potential research problems through free-flowing discussions and idea generation (Jones & Childers, 1989). 3. Researchers can collect data from target populations using surveys or questionnaires to determine their needs, concerns, or areas requiring further investigation (Bell et al., 2017). 4. Through observations and experiments researchers may uncover specific issues or problems within a given context that need further investigation (Babbie, 2016). 5. Identifying and involving key stakeholders in the research topic enables researchers to understand their perspectives and interests, which can aid in defining relevant research problems (Reed et al., 2009).

Main research highlights of our paper are: 1. Problem Addressed: The paper focuses on reducing "hallucinations" in text summarization, where hallucinations refer to generating information not present in the source documents. 2. Dataset Used: The research utilizes the PubMed dataset, which includes long scientific documents and their abstracts. 3. Techniques Employed: To tackle the issue of hallucinations, the paper incorporates data filtering and a joint approach of entity and summary generation (JAENS) in the fine-tuning process. 4. Model Used: The Longformer Encoder-Decoder (LED) model is fine-tuned to minimize hallucinations and improve the summary quality. 5. Evaluation Metrics: Factual consistency of the summaries is measured using precision-source and F1-target metrics at the entity level, along with other common metrics(ROUGE, BERT, METEOR).

Co-design processes are another form of research – action research. But will that process include people with intellectual, physical and sensory conditions? If there is a reading component, will everyone be able to read and interpret written information? Whether it’s academic research or a workplace survey researchers could be missing out on valuable information. Not everyone can interpret rating scales, or agreement to a statement. And if the survey is online, other barriers to participation can emerge. See link for some tips for inclusive research surveys.

STEPS TO FORMULATION OF RESEARCH PROBLEMS 1. Identify the Broad Topic: Choose a General Area of Interest: Begin by selecting a broad area of interest relevant to your field or objectives. This could be based on gaps in the literature, emerging trends, or specific issues needing exploration. Consider Relevance and Feasibility: Ensure the topic is relevant to current discussions and feasible given your resources and time constraints. 2. Conduct Preliminary Research: Review Existing Literature: Conduct a preliminary review of existing studies, articles, and reports to understand what has already been done. This helps in identifying gaps and areas that require further investigation. Identify Key Concepts and Variables: Determine the main concepts, variables, and terminologies used in previous research to familiarize yourself with the topic. 3. Narrow Down the Topic: Specify the Scope: Narrow down the broad topic to a more specific aspect that is manageable and focused. Consider specific populations, contexts, or variables. Focus on Specific Questions or Issues: Identify particular questions or issues within the broad topic that are significant and under-explored. 4. Formulate the Research Problem: State the Problem Clearly: Develop a clear and concise statement of the research problem. This statement should articulate the issue or gap that your research aims to address. Explain the Significance: Describe why the problem is important. Explain its implications for the field, policy, practice, or society. IS IT HELPFUL? ANTICIPATE FOR THE CONCLUDING PART IN THE NEXT POST #research #researchproblem #data #datagik