A hands-on guide to doing content analysis
TL;DR: This manuscript is to provide a practical hands-on example of qualitative content analysis to aid novice qualitative researchers in their task.
About: This article is published in African Journal of Emergency Medicine.The article was published on 2017-09-01 and is currently open access. It has received 1100 citations till now. The article focuses on the topics: Qualitative research.
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TL;DR: The qualitative data analysis method of content analysis is described, which can be useful to pharmacy educators because of its application in the investigation of a wide variety of data sources, including textual, visual, and audio files.
Abstract: Objective. In the course of daily teaching responsibilities, pharmacy educators collect rich data that can provide valuable insight into student learning. This article describes the qualitative data analysis method of content analysis, which can be useful to pharmacy educators because of its application in the investigation of a wide variety of data sources, including textual, visual, and audio files. Findings. Both manifest and latent content analysis approaches are described, with several examples used to illustrate the processes. This article also offers insights into the variety of relevant terms and visualizations found in the content analysis literature. Finally, common threats to the reliability and validity of content analysis are discussed, along with suitable strategies to mitigate these risks during analysis. Summary. This review of content analysis as a qualitative data analysis method will provide clarity and actionable instruction for both novice and experienced pharmacy education researchers.
164 citations
University of Veterinary Medicine Vienna1, Medical University of Vienna2, University of Paris-Sud3, École Normale Supérieure4, International Institute for Applied Systems Analysis5, French Institute for Research in Computer Science and Automation6, Vienna University of Technology7, Jagiellonian University8, University of Warsaw9, Santa Fe Institute10
TL;DR: A specific hierarchical coding scheme for NPIs is developed and a comprehensive structured dataset of government interventions and their respective timelines of implementation is generated via an open library to improve transparency and motivate collaborative validation process.
Abstract: In response to the COVID-19 pandemic, governments have implemented a wide range of non-pharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020.
137 citations
TL;DR: PHAs’ extent of Facebook use for outreach purposes during the COVID-19 pandemic varied among the three PHAs, highlighting the strategies and approaches that other PHAs can potentially adopt.
Abstract: Background: The coronavirus disease (COVID-19) pandemic presents one of the most challenging global crises at the dawn of a new decade. Public health authorities (PHAs) are increasingly adopting the use of social media such as Facebook to rapidly communicate and disseminate pandemic response measures to the public. Understanding of communication strategies across different PHAs and examining the public response on the social media landscapes can help improve practices for disseminating information to the public.
Objective: This study aims to examine COVID-19-related outreach efforts of PHAs in Singapore, the United States, and England, and the corresponding public response to these outreach efforts on Facebook.
Methods: Posts and comments from the Facebook pages of the Ministry of Health (MOH) in Singapore, the Centers for Disease Control and Prevention (CDC) in the United States, and Public Health England (PHE) in England were extracted from January 1, 2019, to March 18, 2020. Posts published before January 1, 2020, were categorized as pre-COVID-19, while the remaining posts were categorized as peri-COVID-19 posts. COVID-19-related posts were identified and classified into themes. Metrics used for measuring outreach and engagement were frequency, mean posts per day (PPD), mean reactions per post, mean shares per post, and mean comments per post. Responses to the COVID-19 posts were measured using frequency, mean sentiment polarity, positive to negative sentiments ratio (PNSR), and positive to negative emotions ratio (PNER). Toxicity in comments were identified and analyzed using frequency, mean likes per toxic comment, and mean replies per toxic comment. Trend analysis was performed to examine how the metrics varied with key events such as when COVID-19 was declared a pandemic.
Results: The MOH published more COVID-19 posts (n=271; mean PPD 5.0) compared to the CDC (n=94; mean PPD 2.2) and PHE (n=45; mean PPD 1.4). The mean number of comments per COVID-19 post was highest for the CDC (mean CPP 255.3) compared to the MOH (mean CPP 15.6) and PHE (mean CPP 12.5). Six major themes were identified, with posts about prevention and safety measures and situation updates being prevalent across the three PHAs. The themes of the MOH’s posts were diverse, while the CDC and PHE posts focused on a few themes. Overall, response sentiments for the MOH posts (PNSR 0.94) were more favorable compared to response sentiments for the CDC (PNSR 0.57) and PHE (PNSR 0.55) posts. Toxic comments were rare (0.01%) across all PHAs.
Conclusions: PHAs’ extent of Facebook use for outreach purposes during the COVID-19 pandemic varied among the three PHAs, highlighting the strategies and approaches that other PHAs can potentially adopt. Our study showed that social media analysis was capable of providing insights about the communication strategies of PHAs during disease outbreaks.
98 citations
Cites methods from "A hands-on guide to doing content a..."
...First, the principal coder reviewed the contents of the COVID-19 posts by PHAs and assigned the relevant themes [34]....
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TL;DR: The results show that the majority of Andalusian local governments have an official corporate Twitter account with certain level of activity, and there is no significant relationship between the population of a municipality and its citizen's engagement, but the particular media and content types generate higher engagement than others.
91 citations
TL;DR: In this paper, the authors develop a theoretical framework of policy implementation that combines collaboration from public and private sectors to efficiently deal with urgent crises such as COVID-19, where the role of new institutions prompted by policy failure precedence (Time 1) that at a later time period (Time 2) allow for the activation of PPPs with the aim to extend the political life of incumbent leaderships.
78 citations
References
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TL;DR: The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
Abstract: Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
31,398 citations
"A hands-on guide to doing content a..." refers methods in this paper
...Inspired primarily by descriptions of ‘‘conventional content analysis” in Hsieh and Shannon [3], ‘‘inductive content analysis” in Elo and Kyngäs [5] and ‘‘qualitative content analysis of an interview text” in Graneheim and Lundman [1], we have written this paper to help the novice qualitative researcher navigate the uncertainty in-between the steps of qualitative content analysis....
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Book•
01 Jan 1980
TL;DR: History Conceptual Foundations Uses and Kinds of Inference The Logic of Content Analysis Designs Unitizing Sampling Recording Data Languages Constructs for Inference Analytical Techniques The Use of Computers Reliability Validity A Practical Guide
Abstract: History Conceptual Foundations Uses and Kinds of Inference The Logic of Content Analysis Designs Unitizing Sampling Recording Data Languages Constructs for Inference Analytical Techniques The Use of Computers Reliability Validity A Practical Guide
25,749 citations
TL;DR: An overview of important concepts related to qualitative content analysis is provided and measures to achieve trustworthiness (credibility, dependability and transferability) throughout the steps of the research procedure are proposed.
16,695 citations
"A hands-on guide to doing content a..." refers background or methods in this paper
...Providing such a table or figure supports the rigor of your study [1] and is an element greatly appreciated by reviewers and research consumers....
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...Some content analysis sources warn researchers against short meaning units, claiming that this can lead to fragmentation [1]....
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...Inspired primarily by descriptions of ‘‘conventional content analysis” in Hsieh and Shannon [3], ‘‘inductive content analysis” in Elo and Kyngäs [5] and ‘‘qualitative content analysis of an interview text” in Graneheim and Lundman [1], we have written this paper to help the novice qualitative researcher navigate the uncertainty in-between the steps of qualitative content analysis....
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TL;DR: Inductive content analysis is used in cases where there are no previous studies dealing with the phenomenon or when it is fragmented, and a deductive approach is useful if the general aim was to test a previous theory in a different situation or to compare categories at different time periods.
Abstract: Aim This paper is a description of inductive and deductive content analysis. Background Content analysis is a method that may be used with either qualitative or quantitative data and in an inductive or deductive way. Qualitative content analysis is commonly used in nursing studies but little has been published on the analysis process and many research books generally only provide a short description of this method. Discussion When using content analysis, the aim was to build a model to describe the phenomenon in a conceptual form. Both inductive and deductive analysis processes are represented as three main phases: preparation, organizing and reporting. The preparation phase is similar in both approaches. The concepts are derived from the data in inductive content analysis. Deductive content analysis is used when the structure of analysis is operationalized on the basis of previous knowledge. Conclusion Inductive content analysis is used in cases where there are no previous studies dealing with the phenomenon or when it is fragmented. A deductive approach is useful if the general aim was to test a previous theory in a different situation or to compare categories at different time periods.
14,963 citations
"A hands-on guide to doing content a..." refers methods in this paper
...Inspired primarily by descriptions of ‘‘conventional content analysis” in Hsieh and Shannon [3], ‘‘inductive content analysis” in Elo and Kyngäs [5] and ‘‘qualitative content analysis of an interview text” in Graneheim and Lundman [1], we have written this paper to help the novice qualitative researcher navigate the uncertainty in-between the steps of qualitative content analysis....
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Book•
01 Jan 1989
TL;DR: In this article, the authors present a comprehensive review of the literature on content analysis in the field of qualitative research, focusing on the role of focus groups and focus groups in the research process.
Abstract: IN THIS SECTION: 1.) BRIEF 2.) COMPREHENSIVE BRIEF TABLE OF CONTENTS: Chapter 1: Introduction Chapter 2: Designing Qualitative Research Chapter 3: Ethical Issues Chapter 4: A Dramaturgical Look at Interviewing Chapter 5: Focus Group Interviewing Chapter 6: Ethnographic Field Strategies Chapter 7: Action Research Chapter 8: Unobtrusive Measures in Research Chapter 9: Social Historical Research and Oral Traditions Chapter 10: Case Studies Chapter 11: An Introduction to Content Analysis Chapter 12: Writing Research Papers: Sorting the Noodles from the Soup COMPREHENSIVE TABLE OF CONTENTS: Chapter 1: Introduction Quantitative Versus Qualitative Schools of Thought Use of Triangulation in Research Methodology Qualitative Strategies: Defining an Orientation From a Symbolic Interactionist Perspective Why Use Qualitative Methods? A Plan of Presentation Chapter 2: Designing Qualitative Research Theory and Concepts Ideas and Theory Reviewing the Literature Evaluating Web Sites Content versus Use Theory, Reality, and the Social World Framing Research Problems Operationalization and Conceptualization Designing Projects Data Collection and Organization Data Storage, Retrieval, and Analysis Dissemination Trying It Out Chapter 3: Ethical Issues Research Ethics in Historical Perspective From Guidelines to Law: Regulations on the Research Process Institutional Review Boards (IRBs) Ethical Codes Some Common Ethical Concerns in Behavioral Research New Areas for Ethical Concern: Cyberspace Informed Consent and Implied Consent Confidentiality and Anonymity Securing the Data Objectivity and Careful Research Design Trying It Out Chapter 4: A Dramaturgical Look at Interviewing Dramaturgy and Interviewing Types of Interviews The Data Collection Instrument Guideline Development Communicating Effectively A Few Common Problems in Question Formulation Pretesting the Schedule Long Versus Short Interviews Telephone Interviews Computer Assisted Interviewing Conducting an Interview: A Natural or an Unnatural Communication? The Dramaturgical Interview The Interviewer's Repertoire Know Your Audience Analyzing Data Obtained from the Dramaturgical Interview Trying It Out Chapter 5: Focus Group Interviewing What are Focus Groups? Working With a Group The Evolution of Focus Group Interviews Facilitating Focus Group Dynamics: How Focus Groups Work The Moderator's Guide Basic Ingredients in Focus Groups Analyzing Focus Group Data Confidentiality and Focus Group Interviews Recent Trends in Focus Groups: Online Focus Groups Trying It Out Chapter 6: Ethnographic Field Strategies Accessing a Field Setting: Getting In Reflectivity and Ethnography Critical Ethnography Becoming Invisible Other Dangers During Ethnographic Research Watching, Listening, and Learning How to Learn: What to Watch and Listen For Computers and Ethnography OnLine Ethnography Analyzing Ethnographic Data Other Analysis Strategies: Typologies, Sociograms, and Metaphors Disengaging: Getting Out Trying It Out Chapter 7: Action Research The Basics of Action Research Identifying the Research Question(s) Gathering the Information to Answer the Question(s) Analyzing and Interpreting the Information Sharing the Results with the Participants When to Use and When Not to Use Action Research The Action Researcher's Role Types of Action Research Photovoice and Action Research Action Research: A Reiteration Trying It Out Chapter 8: Unobtrusive Measures in Research Archival Strategies Physical Erosion and accretion: Human Traces as Data Sources Trying It Out Chapter 9: Social Historical Research and Oral Traditions What Is Historical Research? Life Histories and Social History What Are the Sources of Data for Historical Researchers? Doing Historiography: Tracing Written History as Data What Are Oral Histories? Trying It Out Chapter 10: Case Studies The Nature of Case Studies Theory and Case Studies The Individual Case Study Intrinsic, Instrumental, and Collective Case Studies Case Study Design Types Designing Case Studies The Scientific Benefit of Case Studies Case Studies of Organizations Case Studies of Communities Trying It Out Chapter 11: An Introduction to Content Analysis What is Content Analysis? Analysis of Qualitative Data Content Analysis as a Technique Content Analysis: Quantitative or Qualitative? Communication Components What to Count: Levels and Units of Analysis Category Development: Building Grounded Theory Discourse Analysis and Content Analysis Open Coding Coding Frames Stages in the Content Analysis Process Strengths and Weaknesses of the Content Analysis Process Computers and Qualitative Analysis Qualitative Research at the Speed of Light Trying It Out Chapter 12: Writing Research Papers: Sorting the Noodles from the Soup Plagiarism: What It Is, Why It's Bad, and How to Avoid It Identifying the Purpose of the Writing: Arranging the Noodles Delineating a Supportive Structure: Visual Signals for the Reader Terms and Conditions Presenting Research Material A Word About the Content of Papers and Articles Write It, Rewrite It, Then Write It Again! A Few Writing Hints A Final Note
14,765 citations