Do you have responses to open-ended questions or want to use qualitative data to evaluate CE/QI interventions? Qualitative Analysis Boot Camp at the ACEHP 2013 meeting in San Francisco on 1 February has tools to get you started.
Qualitative data analysis involves non-numerical assessment of observations from techniques like participant observation, content analysis, and interviews. Key aspects of analysis include discovering patterns in the data, grounded theory method, and semiotics. Grounded theory method aims to generate or discover a theory through successive levels of data analysis and conceptual development. It involves comparing incidents, integrating categories and properties, delimiting the theory, and writing the theory.
This document provides an overview of qualitative data analysis techniques. It discusses how qualitative analysis differs from quantitative analysis in that the data is textual rather than numerical. Qualitative analysis is inductive and focuses on understanding participants' perspectives through an emic lens. The analysis is iterative and progressive, with the researcher continually refining their focus based on initial interpretations of the data. There is no single correct way to analyze qualitative data, as it involves both science and art. Techniques include coding, categorizing, examining relationships, and using computer assistance programs, while ensuring reflexivity and getting critical feedback.
Let's Talk Research 2015 -Juliet Goldbart - Introduction To Qualitative Metho...NHSNWRD
Introduction To Qualitative Methods: Different Approaches For Different Contexts
Jois Stansfield, Maxine Holt, Nigel Cox, Suzanne Gough, Juliet Goldbart, MMU
Messy Research: How to Make Qualitative Data Quantifiable and Make Messy Data...Gigi Johnson
This document discusses qualitative research methods for business. It addresses challenges in making qualitative data understandable for real decisions. It discusses why businesses conduct research, how to determine what data and analysis is needed, and issues with determining "truth" in business contexts. Finally, it discusses four types of qualitative data and focuses on making qualitative data more quantitative by addressing issues like validity, sample sizes, and coding consistency.
Making Sense of It All: Analyzing Qualitative DataGeorge Hayhoe
Qualitative methodologies are becoming increasingly important in our discipline. Because they are based on techniques that technical communicators commonly use, everyone in the profession finds these methods familiar and understandable.
This workshop will draw on that familiarity and comprehension to show practitioners how to analyze and interpret the data collected from interviews, focus groups, open-ended questionnaires, and communication artifacts. The workshop is based on simple, proven methods that produce meaningful results that can be used to inform decisions about product design and delivery.
First, the moderators will review examples of qualitative methods and data. Then, the moderators will explain how to organize data for analysis. Finally, the moderators will describe Content Analysis, a technique for analyzing and interpreting the data.
With this background, participants will work in teams to analyze and interpret data using Content Analysis. Then, the teams will report the results of their analysis and interpretation.
This document provides an introduction to quantitative and qualitative research methods. It explains that the research approach chosen depends on the research questions, underlying philosophy, and skills of the researcher. Quantitative research uses numerical data and statistical analysis, while qualitative research uses words and focuses on understanding phenomena. Both have advantages and limitations. The document also discusses research design principles, data sources, analysis techniques, and key aspects to consider for quantitative and qualitative approaches.
Qualitative data analysis involves non-numerical assessment of observations from techniques like participant observation, content analysis, and interviews. Key aspects of analysis include discovering patterns in the data, grounded theory method, and semiotics. Grounded theory method aims to generate or discover a theory through successive levels of data analysis and conceptual development. It involves comparing incidents, integrating categories and properties, delimiting the theory, and writing the theory.
This document provides an overview of qualitative data analysis techniques. It discusses how qualitative analysis differs from quantitative analysis in that the data is textual rather than numerical. Qualitative analysis is inductive and focuses on understanding participants' perspectives through an emic lens. The analysis is iterative and progressive, with the researcher continually refining their focus based on initial interpretations of the data. There is no single correct way to analyze qualitative data, as it involves both science and art. Techniques include coding, categorizing, examining relationships, and using computer assistance programs, while ensuring reflexivity and getting critical feedback.
Let's Talk Research 2015 -Juliet Goldbart - Introduction To Qualitative Metho...NHSNWRD
Introduction To Qualitative Methods: Different Approaches For Different Contexts
Jois Stansfield, Maxine Holt, Nigel Cox, Suzanne Gough, Juliet Goldbart, MMU
Messy Research: How to Make Qualitative Data Quantifiable and Make Messy Data...Gigi Johnson
This document discusses qualitative research methods for business. It addresses challenges in making qualitative data understandable for real decisions. It discusses why businesses conduct research, how to determine what data and analysis is needed, and issues with determining "truth" in business contexts. Finally, it discusses four types of qualitative data and focuses on making qualitative data more quantitative by addressing issues like validity, sample sizes, and coding consistency.
Making Sense of It All: Analyzing Qualitative DataGeorge Hayhoe
Qualitative methodologies are becoming increasingly important in our discipline. Because they are based on techniques that technical communicators commonly use, everyone in the profession finds these methods familiar and understandable.
This workshop will draw on that familiarity and comprehension to show practitioners how to analyze and interpret the data collected from interviews, focus groups, open-ended questionnaires, and communication artifacts. The workshop is based on simple, proven methods that produce meaningful results that can be used to inform decisions about product design and delivery.
First, the moderators will review examples of qualitative methods and data. Then, the moderators will explain how to organize data for analysis. Finally, the moderators will describe Content Analysis, a technique for analyzing and interpreting the data.
With this background, participants will work in teams to analyze and interpret data using Content Analysis. Then, the teams will report the results of their analysis and interpretation.
This document provides an introduction to quantitative and qualitative research methods. It explains that the research approach chosen depends on the research questions, underlying philosophy, and skills of the researcher. Quantitative research uses numerical data and statistical analysis, while qualitative research uses words and focuses on understanding phenomena. Both have advantages and limitations. The document also discusses research design principles, data sources, analysis techniques, and key aspects to consider for quantitative and qualitative approaches.
This document provides an overview of a quantitative methods course, including its objectives, reference materials, syllabus, and suggested schedule. The course aims to equip students with concepts, tools, and techniques for managerial decision making. Key topics covered include probability, sampling, estimation, hypothesis testing, analysis of variance, correlation, regression, time series analysis, decision trees, and linear programming. The syllabus outlines these topics in detail and includes case studies to supplement the theoretical concepts. The course is worth 3 credits and will meet for 30 sessions over one semester.
Qualitative data analysis research schoolkelvinbotchie
1. The document discusses qualitative data analysis and provides guidance on planning an analytic strategy. It emphasizes that analysis is an ongoing process that develops over time as research questions are answered and refined.
2. Several forms of qualitative analysis are described, including theme analysis to develop conceptual categories across different data types, and discourse analysis which focuses on specific textual features.
3. Effective analysis involves coding data into categories, using the constant comparative method to clarify ideas, and assessing progress towards answering research questions.
This document provides an overview of quantitative research methods, with a focus on surveys. It discusses different types of surveys, including personal interviews, telephone interviews, self-administered questionnaires, and internet surveys. It highlights advantages and disadvantages of different survey methods. The document also discusses issues with cross-cultural research and conducting surveys across cultures. Key challenges include differences in language, response styles, and cultural appropriateness of survey questions.
Quantitative and qualitative analysis of dataNisha M S
This document provides an overview of several qualitative and quantitative research methods and analysis techniques. It discusses interpretative phenomenological analysis (IPA) for qualitative analysis, which aims to explore participants' experiences and perspectives while acknowledging the researcher's own biases. It also reviews grounded theory methodology, discourse analysis techniques, and narrative analysis approaches. For quantitative analysis, it outlines organizing data, visual presentation methods, measures of central tendency, measures of variation, and common statistical tests. The document presents steps and considerations for applying these diverse analytical methods to research.
Qualitative research relies on textual data rather than numbers, focusing on accurate information. Quantitative research depends on objective numeric data suitable for statistics. It is important for media researchers to collect both qualitative and quantitative data to provide depth, cover a wide range of needed data effectively, and make results more reliable and understandable for audiences. Collecting both surveyed and textual information creates a more effective research project than only one type, as each provides different valuable insights.
Making qualitative analysis more transparent by using NVivoQSR International
This document provides an overview of using NVivo software to conduct transparent qualitative data analysis. It discusses using a team or solo approach, documenting the analytic process through memos and a detailed codebook, coding interviews and other sources, running queries to identify relationships between codes and themes, and making the analysis iterative and supported by the source data. The goal is to facilitate a rigorous qualitative analysis process that meets standards for trustworthy qualitative research.
Here is my coding of the passage about Amanda:
1. Getting pregnant
2. Uncertainty
3. Settling down
4. Lifestyle
5. Uncertainty
6. Lifestyle
7. Uncertainty
8. Uncertainty
To segment effectively, you need to understand what drives the segments, not just how to measure them. That's where qualitative insight comes in.
Please credit the author if you use the material. Some images are subject to copyright.
The document discusses the importance of rigor and robustness in research. It aims to provide insight into the meaning of rigor and how it can be maintained throughout the different stages of the research process, regardless of the research approach or paradigm used. Specifically, it discusses strategies for achieving rigor in areas like sampling techniques, data collection, data analysis, and reporting findings. Maintaining rigor is important for producing robust and reliable research results.
Qualitative data analysis: many approaches to understand user insightsAgnieszka Szóstek
The fifth lecture at HITLab, Canterbury University in New Zealand was all about how important it is to run a proper analysis of the qualitative data. We discussed the value in looking at data from individual (phenomenological) perspective versus combined (reductionist) perspective. But we agreed that regardless of the chosen approach it is crucial to look at the data from more than just one perspective to be sure the interpretation is not biased by researcher's on view of the world.
This document discusses qualitative data analysis (QDA) procedures and types. It outlines the 5 main steps of QDA: 1) organize data, 2) identify a framework, 3) sort data into the framework, 4) use the framework for descriptive analysis, and 5) conduct second order analysis. It also describes common types of QDA like content analysis, narrative analysis, and discourse analysis. Finally, it lists some commonly used computer software for assisting with QDA tasks like coding, data storage, and reporting.
Analyzing observational data during qualitative researchWafa Iqbal
This document discusses qualitative data analysis methods. It explains that qualitative data analysis explores and interprets complex data from sources like interviews and observations to generate new understandings without quantification. The generic process of analysis involves organizing, reading, and coding the data by assigning labels to chunks of information to develop themes and descriptions. Coding is a primary element of analysis and allows the researcher to summarize and synthesize the data. Developing themes is also part of the analysis process and involves discovering core and peripheral elements of themes from the data.
This document discusses key concepts in research methodology. It defines a focus group discussion as a method to collect primary data from a representative group with a moderator. An ideal focus group has 8-12 members who are strangers from similar backgrounds. It also outlines the steps to test a hypothesis, including specifying the null and alternative hypotheses, setting the significance level, calculating test statistics and p-values, and drawing a conclusion. Exploratory research designs explored include secondary resource analysis, case studies, expert opinion surveys, and focus group discussions. Guidelines for effective report writing and types of comparative and non-comparative scales are also discussed.
The document summarizes findings from a focus group discussion on sample routers. Key points:
1. Participants use multiple sample sources for consistency and control over the process. Routers were seen as potentially increasing feasibility but also introducing bias.
2. Consistency of data was the top concern, with participants discussing various methods to maintain it like sample blending and pretesting.
3. There was apprehension about a lack of transparency from routers regarding prescreening and other studies running simultaneously. Participants wanted more metrics but felt unqualified to evaluate them.
L. O'Keefe Writing Sample - Qualitative Research NarrativeLindsay O'Keefe
This document provides an overview of qualitative research methods that can be used to evaluate learning programs at the John G. Shedd Aquarium. It describes several common qualitative methods including interviews, observations, document/content analysis. For each method, it outlines what it is, when it is useful, pros and cons, analysis procedures, and provides examples of how each method has been used to evaluate programs at other museums. The overall purpose is to inform staff at Shedd Aquarium about qualitative evaluation methods that could be applied to better understand their learning programs.
This document provides an introduction to qualitative research methods. It defines qualitative research as investigating social phenomena and human problems through methodology that collects descriptive data in words from observations and interviews. Key characteristics of qualitative research include an open-ended research question, a small purposeful sample, collection of data through semi-structured and unstructured instruments, and presentation of results descriptively. The document outlines common qualitative research approaches like grounded theory, phenomenology, ethnography, case studies, and action research. It also discusses sampling, data collection methods, and analysis in qualitative research.
This document provides an overview of qualitative research and its applications in continuing education for healthcare professionals (CEHP). It discusses the qualitative approach, data collection methods like interviews, analysis techniques including coding, and reporting results. Qualitative research explores experiences and perceptions through open-ended questions to provide deep insights. It is well-suited for needs assessments, intervention development, and evaluation across CEHP phases. The document reviews online data collection tools, question types, interviewer behavior, and software to assist with coding, organization, and visualization of results.
Risk of Bias_StaR Child Health Summit_07May12michele_hamm
Michele Hamm presented at the StaR Child Health Summit in Winnipeg, Manitoba on May 7, 2012. The presentation discussed the growing evidence that pediatric clinical trials often have a high risk of bias, which can lead to overestimations of treatment benefits or underestimations of harms. Hamm described a mixed methods study involving surveys and interviews with pediatric trialists to understand the barriers and facilitators they face in designing and conducting methodologically rigorous trials. The study found that a lack of formal research training, insufficient funding, and negative research cultures can contribute to higher risks of bias in trials. Developing cohesive study teams, reliable review processes
This document provides an overview of a quantitative methods course, including its objectives, reference materials, syllabus, and suggested schedule. The course aims to equip students with concepts, tools, and techniques for managerial decision making. Key topics covered include probability, sampling, estimation, hypothesis testing, analysis of variance, correlation, regression, time series analysis, decision trees, and linear programming. The syllabus outlines these topics in detail and includes case studies to supplement the theoretical concepts. The course is worth 3 credits and will meet for 30 sessions over one semester.
Qualitative data analysis research schoolkelvinbotchie
1. The document discusses qualitative data analysis and provides guidance on planning an analytic strategy. It emphasizes that analysis is an ongoing process that develops over time as research questions are answered and refined.
2. Several forms of qualitative analysis are described, including theme analysis to develop conceptual categories across different data types, and discourse analysis which focuses on specific textual features.
3. Effective analysis involves coding data into categories, using the constant comparative method to clarify ideas, and assessing progress towards answering research questions.
This document provides an overview of quantitative research methods, with a focus on surveys. It discusses different types of surveys, including personal interviews, telephone interviews, self-administered questionnaires, and internet surveys. It highlights advantages and disadvantages of different survey methods. The document also discusses issues with cross-cultural research and conducting surveys across cultures. Key challenges include differences in language, response styles, and cultural appropriateness of survey questions.
Quantitative and qualitative analysis of dataNisha M S
This document provides an overview of several qualitative and quantitative research methods and analysis techniques. It discusses interpretative phenomenological analysis (IPA) for qualitative analysis, which aims to explore participants' experiences and perspectives while acknowledging the researcher's own biases. It also reviews grounded theory methodology, discourse analysis techniques, and narrative analysis approaches. For quantitative analysis, it outlines organizing data, visual presentation methods, measures of central tendency, measures of variation, and common statistical tests. The document presents steps and considerations for applying these diverse analytical methods to research.
Qualitative research relies on textual data rather than numbers, focusing on accurate information. Quantitative research depends on objective numeric data suitable for statistics. It is important for media researchers to collect both qualitative and quantitative data to provide depth, cover a wide range of needed data effectively, and make results more reliable and understandable for audiences. Collecting both surveyed and textual information creates a more effective research project than only one type, as each provides different valuable insights.
Making qualitative analysis more transparent by using NVivoQSR International
This document provides an overview of using NVivo software to conduct transparent qualitative data analysis. It discusses using a team or solo approach, documenting the analytic process through memos and a detailed codebook, coding interviews and other sources, running queries to identify relationships between codes and themes, and making the analysis iterative and supported by the source data. The goal is to facilitate a rigorous qualitative analysis process that meets standards for trustworthy qualitative research.
Here is my coding of the passage about Amanda:
1. Getting pregnant
2. Uncertainty
3. Settling down
4. Lifestyle
5. Uncertainty
6. Lifestyle
7. Uncertainty
8. Uncertainty
To segment effectively, you need to understand what drives the segments, not just how to measure them. That's where qualitative insight comes in.
Please credit the author if you use the material. Some images are subject to copyright.
The document discusses the importance of rigor and robustness in research. It aims to provide insight into the meaning of rigor and how it can be maintained throughout the different stages of the research process, regardless of the research approach or paradigm used. Specifically, it discusses strategies for achieving rigor in areas like sampling techniques, data collection, data analysis, and reporting findings. Maintaining rigor is important for producing robust and reliable research results.
Qualitative data analysis: many approaches to understand user insightsAgnieszka Szóstek
The fifth lecture at HITLab, Canterbury University in New Zealand was all about how important it is to run a proper analysis of the qualitative data. We discussed the value in looking at data from individual (phenomenological) perspective versus combined (reductionist) perspective. But we agreed that regardless of the chosen approach it is crucial to look at the data from more than just one perspective to be sure the interpretation is not biased by researcher's on view of the world.
This document discusses qualitative data analysis (QDA) procedures and types. It outlines the 5 main steps of QDA: 1) organize data, 2) identify a framework, 3) sort data into the framework, 4) use the framework for descriptive analysis, and 5) conduct second order analysis. It also describes common types of QDA like content analysis, narrative analysis, and discourse analysis. Finally, it lists some commonly used computer software for assisting with QDA tasks like coding, data storage, and reporting.
Analyzing observational data during qualitative researchWafa Iqbal
This document discusses qualitative data analysis methods. It explains that qualitative data analysis explores and interprets complex data from sources like interviews and observations to generate new understandings without quantification. The generic process of analysis involves organizing, reading, and coding the data by assigning labels to chunks of information to develop themes and descriptions. Coding is a primary element of analysis and allows the researcher to summarize and synthesize the data. Developing themes is also part of the analysis process and involves discovering core and peripheral elements of themes from the data.
This document discusses key concepts in research methodology. It defines a focus group discussion as a method to collect primary data from a representative group with a moderator. An ideal focus group has 8-12 members who are strangers from similar backgrounds. It also outlines the steps to test a hypothesis, including specifying the null and alternative hypotheses, setting the significance level, calculating test statistics and p-values, and drawing a conclusion. Exploratory research designs explored include secondary resource analysis, case studies, expert opinion surveys, and focus group discussions. Guidelines for effective report writing and types of comparative and non-comparative scales are also discussed.
The document summarizes findings from a focus group discussion on sample routers. Key points:
1. Participants use multiple sample sources for consistency and control over the process. Routers were seen as potentially increasing feasibility but also introducing bias.
2. Consistency of data was the top concern, with participants discussing various methods to maintain it like sample blending and pretesting.
3. There was apprehension about a lack of transparency from routers regarding prescreening and other studies running simultaneously. Participants wanted more metrics but felt unqualified to evaluate them.
L. O'Keefe Writing Sample - Qualitative Research NarrativeLindsay O'Keefe
This document provides an overview of qualitative research methods that can be used to evaluate learning programs at the John G. Shedd Aquarium. It describes several common qualitative methods including interviews, observations, document/content analysis. For each method, it outlines what it is, when it is useful, pros and cons, analysis procedures, and provides examples of how each method has been used to evaluate programs at other museums. The overall purpose is to inform staff at Shedd Aquarium about qualitative evaluation methods that could be applied to better understand their learning programs.
This document provides an introduction to qualitative research methods. It defines qualitative research as investigating social phenomena and human problems through methodology that collects descriptive data in words from observations and interviews. Key characteristics of qualitative research include an open-ended research question, a small purposeful sample, collection of data through semi-structured and unstructured instruments, and presentation of results descriptively. The document outlines common qualitative research approaches like grounded theory, phenomenology, ethnography, case studies, and action research. It also discusses sampling, data collection methods, and analysis in qualitative research.
This document provides an overview of qualitative research and its applications in continuing education for healthcare professionals (CEHP). It discusses the qualitative approach, data collection methods like interviews, analysis techniques including coding, and reporting results. Qualitative research explores experiences and perceptions through open-ended questions to provide deep insights. It is well-suited for needs assessments, intervention development, and evaluation across CEHP phases. The document reviews online data collection tools, question types, interviewer behavior, and software to assist with coding, organization, and visualization of results.
Risk of Bias_StaR Child Health Summit_07May12michele_hamm
Michele Hamm presented at the StaR Child Health Summit in Winnipeg, Manitoba on May 7, 2012. The presentation discussed the growing evidence that pediatric clinical trials often have a high risk of bias, which can lead to overestimations of treatment benefits or underestimations of harms. Hamm described a mixed methods study involving surveys and interviews with pediatric trialists to understand the barriers and facilitators they face in designing and conducting methodologically rigorous trials. The study found that a lack of formal research training, insufficient funding, and negative research cultures can contribute to higher risks of bias in trials. Developing cohesive study teams, reliable review processes
In this presentation, we go over the most common qualitative research designs. We go over the main components of Chapter 3, including methodology and rationale, the role of the researcher, the selection of participants, instrumentation, procedure, data analysis plan, and issues of trustworthiness.
Evidence based medicine involves integrating clinical expertise with the best available research evidence and patient values. It aims to apply the most appropriate interventions for individual patients based on scientific evidence. The key steps involve formulating an answerable clinical question using the PICO framework, searching for and critically appraising the relevant evidence, and applying the findings to clinical practice. While evidence based medicine improves clinical decision making, it also faces criticisms such as being time-consuming and potentially reducing clinical reasoning.
This document provides an overview of how to conduct research. It defines research as systematically collecting and analyzing data to increase understanding. It explains that as students, future practitioners, and educated citizens, understanding research is important. The document outlines the basic steps of a research project including finding a topic, formulating questions, defining the population, selecting a design and measurements, gathering evidence, interpreting evidence, and reporting findings. It also discusses key research concepts like variables, hypotheses, sampling, and quantitative and qualitative methodologies.
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A Qualitative Research Question Paper
This presentation, presented to senior thesis students at UC Berkeley, reviews the uses of qualitative research methods such as ethnography in public health, walking students through methods, sampling, ensuring rigor, and analysis with CAQDAS software such as Atlas.ti
The document discusses key concepts in research methods, including quantitative and qualitative research. It defines quantitative research as using numerical data to test hypotheses, while qualitative research uses words to understand phenomena. Some advantages of quantitative research are its validity and reliability, while its disadvantages include difficulties measuring human behavior. Qualitative research allows deep exploration but lacks rigor and generalizability. Overall, the document provides an overview of important research terminology and compares different research approaches.
There are key differences between qualitative and quantitative research. Quantitative research generates numerical/statistical data through tools like questionnaires and focuses on measuring and analyzing target concepts precisely. Qualitative research generates non-numerical data like words through interviews and focuses on understanding human behavior and reasons for it through a subjective approach. While quantitative research aims to generalize findings, qualitative research provides in-depth descriptions and explores phenomena. The choice depends on the research question - qualitative is used for exploratory studies, while quantitative is used for conclusive studies later in the research process.
A guide to understand and application of Research Methodology for a research paper writing. This presentation has been prepared for a live webinar organised on 8th May, 2021.
This document provides an overview of qualitative analysis methods for coding interview and document data. It begins with an agenda for covering two main qualitative approaches, coding exercises, slides on qualitative analysis, and potential brainstorming and affinity diagramming exercises if time allows. It then discusses common features of qualitative analytic methods including affixing codes, noting reflections, sorting materials to identify patterns, and gradually developing generalizations. Finally, it provides details on coding and categorization procedures, the iterative nature of qualitative analysis, and ensuring the credibility and rigor of qualitative findings.
This document outlines the components and content of a research protocol. It discusses including a title, abstract, introduction/objectives, literature review, methodology, references, and ethics considerations. The methodology section should describe the study design, variables, measurements, subjects/participants, sample size calculation, and data analysis plan. Developing a thorough protocol is important to clarify the research question, compile existing knowledge, decide on a study design, and apply for funding. It provides a guide for investigators to arrive at comparable conclusions.
This document provides an introduction to key concepts in primary care research. It discusses how to formulate a research question and understand the differences between quantitative and qualitative research approaches. The major steps in the research process are outlined as identification of a problem, literature review, specifying questions/hypotheses, determining methodology, data collection and analysis, and interpreting findings. Common quantitative study designs like cross-sectional, case control, cohort, and randomized controlled trials are explained. The document also covers using secondary data sources for research.
This document provides an introduction to key concepts in primary care research. It discusses how to formulate a research question and understand the differences between quantitative and qualitative research approaches. The major steps in the research process are outlined as identification of a problem, literature review, specifying questions/hypotheses, determining methodology, data collection and analysis, and interpreting findings. Common quantitative study designs like cross-sectional, case control, cohort, and randomized controlled trials are explained. The document also covers using secondary data sources for research.
This document provides an introduction to key concepts in primary care research. It discusses how to formulate a research question and understand the differences between quantitative and qualitative research approaches. The major steps in the research process are outlined, including identifying a problem, conducting a literature review, determining a study design and methodology, collecting and analyzing data, and interpreting findings. Common quantitative study designs like cross-sectional, case-control, cohort, and randomized controlled trials are explained. The document also covers using secondary data sources for research.
The document provides an overview of research methodologies and methods. It discusses the differences between methodologies and methods, with methodologies representing the overall approach and lens for analyzing results, and methods being the specific tools used to collect data. Both qualitative and quantitative research are covered, with qualitative focusing on meanings and in-depth insights while quantitative examines relationships and trends. Key aspects of choosing and conducting qualitative research are outlined, including sampling techniques, common analysis methods like coding and triangulation, and examples of qualitative research questions.
Quantitative search and_qualitative_research by mubarakHafiza Abas
The document discusses quantitative and qualitative research methods. Quantitative research aims to quantify data by using structured tools like questionnaires to collect numerical data from large samples that can be statistically analyzed. It focuses on objectively testing hypotheses. Qualitative research collects non-numerical data like descriptions through methods such as interviews and observations to understand peoples' experiences. It focuses on exploring topics in-depth. The document also compares surveys and questionnaires, describing their differences and advantages and disadvantages of various survey methods.
This document provides an overview of research, including definitions of research, the nature and types of business research, and differences between qualitative and quantitative research methods. It discusses scientific research processes and characteristics. The key points are:
- Business research is defined as the systematic and objective process of generating information to aid decision-making. It can describe efforts to investigate and solve specific problems encountered in business settings.
- There are differences between qualitative research, which focuses on depth, meaning and subjectivities, and quantitative research, which relates to numbers that can be quantified.
- Research should be undertaken when time allows, information is inadequate, decisions are important, and research benefits outweigh costs. Ethical considerations like informed consent,
The document outlines the steps to plan a research project on the impact of nutrition on health and performance. It discusses establishing research aims and objectives, determining appropriate data types, choosing research tools, identifying participants, and creating a timeline. The research aims to assess links between nutrition and performance for dancers by exploring their diets, health, awareness of nutrition, and whether nutrition impacts their ability to perform. Both qualitative and quantitative data could be collected through surveys, observations, interviews, and focus groups. The document evaluates different tools and considerations for ensuring reliable, representative, and objective research.
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Custom modules offer the flexibility to extend Odoo's capabilities, address unique requirements, and optimize workflows to align seamlessly with your organization's processes. By leveraging custom modules, businesses can unlock greater efficiency, productivity, and innovation, empowering them to stay competitive in today's dynamic market landscape. In this tutorial, we'll guide you step by step on how to easily download and install modules from the Odoo App Store.
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
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This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
4. Exploration
Unearth a complete and detailed description of the
how and why behind physician, allied healthcare
provider, and patient behavior.
Produce deep answers to research questions that
give voice and layered explanation to the answers
you seek.
5. Qualitative vs. Quantitative
Qualitative Research Quantitative Research
Probing; allowing
Limited probing; pre-
Type of Questions immediate interactive
determined questions
follow up & adjustment
Sample Size Small Any size including large
Information per Varies; Limited to answer
Much
respondent choices
Fewer specialist skills
Administration Requires skilled researcher
required
Follows structured steps;
Type of Analysis subjective and Statistical; objective
interpretative
Type of Research Exploratory, descriptive Descriptive or Causal
6. Why Qualitative?
Patient care is complex
Semi-structured, open ended approach to inquiry
Less limiting - explores beyond pre-selected answer
choices
Interaction - researchers probe and react to study
subject comments
Mixed methods
7. Applications in CEHP
Research Phases Research Subjects
Needs Assessment Physicians
Intervention Development Allied Healthcare Providers
Formative Evaluation Healthcare Staff
Post Intervention Assessment Patients/Caregivers
(“Outcomes”)
Instrument Development
Methodological Focus Help inform development of
Pure Qualitative quantitative tools
Mixed Methods
9. Sample Methodologies/Tools
• Interviews (in person, virtual/online, telephonic)
• Focus Groups (in person, virtual/online facilities)
• Message Boards/Social Media Analysis
• Observation
• Document Analysis
• Mixed-Methods (Qualitative and Quantitative
combination)
10. Online Methodologies
Research methodologies = evolving with
communication styles
Widely-used, often preferred options for
researchers and respondents
Benefits
Cost Savings
Ease for wide geographical representation
Ease for scheduling (no need for travel, sessions tailored
to their availability)
Anonymity = less inhibition / more honesty
13. One-on-One In-Depth Interviews
Whiteboard may
also be filled
with text, video,
images, or
interactive ranking,
posting, or writing
activities. The
interviewee can
move objects
onscreen, as in this
card-sorting
exercise.
17. Coding
Breaking down data into units which are then
grouped according to characteristics
Proceeds linking diverse
observations
Helps with understanding
It’s practical!
Organization = quick access when you need it
for analysis/description.
18. Coding
1st phase: review data:
What’s happening?
What’s important?
What patterns are emerging?
2nd stage: repeat, refine, expand/reject categories
Text can be tagged with >1 code
19. Grounded Theory
Glaser & Straus (1967) – emphasis on developing
theory/explanation from data versus gathering
data to test a theory/hypothesis.
The theory is grounded in reality as represented in
the data
Benefits:
Theory is derived from what speakers do, vs. what is
believed they should do
Ensures the researchers maintain an open mind towards
inquiry vs. imposing existing beliefs on data
20. How can Software Assist?
Methodology
GATHER ORGANIZE ANALYZE VISUALIZE RESULTS
• Rigor
• Validity
• Saturation
21. How can Software Assist?
-Review
-Key Ideas
-Merge
-Reflect
-Refine
-Link
Coding Memoing
Visuals Queries
-Models -Text Search
-Matrices -Word Frequency
-Charts -Matrix
-Coding Comparison
Source: Nvivo (QSR)
25. “Many who had once supported lobotomy began
to disavow it. "It is inconceivable," reported the
American Medical Association, "that any
procedure that effectively destroys the brain could
possibly restore the patient to a normal state."
Lobotomy, one former supporter declared, was
really no more subtle than a gunshot to the head.
Especially vehement were Freudian
psychoanalysts, who condemned lobotomy as a
brutal assault on the brain. But Walter Freeman
had little patience for his critics.”
29. Reporting
Reports = based on trends and relationships
found within the data
Includes:
Trend Description
Respondent Quotes
Visualizations (themes, their relationships,
demographic elements)
Interpretation
30. Reporting: Descriptive
Patient Concern about high blood pressure:
The overwhelming response to the question "Should a
person be concerned about having high blood
pressure?" was "yes." Most people believed that
being unconcerned could result in serious health
problems, specifically heart disease or even death.
"A person can die if they have high blood pressure
because it can cause a stroke or it can cause heart
problems."
31. Reporting: Trends
Patients‟ opinions on how well providers explain a
medication varies from “satisfied” to “very well”
For some patients, the nurse practitioner provides more
detail, as does the pharmacist and the information that
accompanies the medication.
Between the nurse practitioner and the physician,
respondents tend to trust the physician more. In many
cases, it appears that patients with a strong, long, and
trusting relationship with their providers perceive them as
explaining the medication better than those without
an established relationship or who distrust their providers.
32. Reporting: Giving Voice
Provider: “After their bypass surgery, when they have seen
God and all that, they listen, but after they are out of the
hospital and they are going through rehab and they are
fine, that period of after the bypass, they are invincible.”
Patient: “I took [the prescription] to the pharmacy and
……they were only going to give me four pills because it is
so expensive, and I am saying to myself, „why did they give
me this, I am going to die because I will not be able to
afford it?‟
In my head, I said „Oh Lord; please make this work without
any side effects so I can take it.‟”
33. Reporting: Quote Integration
Having a normal blood pressure level:
Living a calm life, feeling relaxed, and avoiding or solving
problems were seen as very effective ways to keep blood
pressure normal. "Be calm in everything. Do not get angry over
something small."
"I try not to have problems with anyone at home, in the street, or
anywhere else. If I were to have a problem with anyone here, my
blood pressure would go up immediately. A person can burst."
Generating theory/explanation, building hypotheses
Acknowledges importance of immediate, practice context
Many, diverse, interacting elements in healthcare, plus distinct organizational cultures, patterns of communication, tacit knowledge etc2. Best way to understand in-depth motivations and feelings of providers and patients3. Unrestrained sharing of information, experience, and viewpoint4. Gain clarity, depth, and a “fuller picture”of understanding - Can improve effectiveness of quantitative research, e.g. use qualitative data to focus quantitative measures5. Provides a blend of statistical quantifying and layered qualitative understanding of motivation, behavior, change – helpful to triangulate data, methods, researchers6. Economical Option
Prior to gran/t/proposal or intervention development – identify + sensitizestakeholders to intervention, secure buy-in, build picture of organizational process, leadershipBaseline assessments e.g. readiness for changeCan identify organizational enablers and facilitators of learning Learner change progressionMay use qualitative data to developquantitative measuresAlso mixed approach to evaluate full impact of initiatives/interventions through blend of statistical quantifying and layered contextual understanding of changeCan help to get a clearer picture of contextual and experiential factors that influence change, learning and practice
Audio: can help increase response rates, maximizes efficient use of resources, reduces interviewer effects, detachment can improve quality of response (more disclosure), researcher can take detailed notes without making respondent feel uncomfortable, faster results [Knox 2009]ReferencesCater JK. SKYPE: a cost-effective method for qualitative research. Rehab, Counselors + Educators Journal. 20011;4: Gill P, Stewart, K.; Treasure, E.; Chadwick, B. Methods of data collection in qualitative research: interview and focus groups. British Dental Journal. 2008;204: 291-295. Hayman B, Wilkes L, Jackson D, Halcomb E. Story-sharing as a method of data collection in qualitative research. Journal of Clinical Nursing. 2012, Vol. 21 Issue1/2:285-287.Meho LI. E-mail interviewing in qualitative research: a methodological discussion. J AmerSoc Info Sci Tech. 2006; 57(10):1284–1295. Musselwhite K, Cuff L, McGregor L, King KM. The telephone interview is an effective method of data collection in clinical nursing research: a discussion paper. Int J Nurs Stud. 2007 Aug;44(6):1064-70. Epub 2006 Jul 17.Novick G. Is there a bias against telephone interviews in qualitative research? Res Nurs Health. 2008;31:391-398.Reeves S, Kuper A, Hodges BD. Qualitative research methodologies: ethnography. BMJ. 2008;337:a1020.
Online adds deeper level of interactivity to the interviews
Online adds deeper level of interactivity to the interviews
A filing system
Interpretation tied closely to data
GATHER- existing research, current information, data sourcesORGANIZE – data sources, coding structure, demograhics, lit reviewANALYZE- coding, queries, memos, valuesVISUALIZERESULTS reports, presentations
GATHER- existing research, current information, data sourcesORGANIZE – data sources, coding structure, demograhics, lit reviewANALYZE- coding, queries, memos, valuesVISUALIZERESULTS reports, presentations