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Documentary Analysis – Methods, Applications and Examples

Table of Contents

Documentary Analysis

Definition:

Documentary analysis, also referred to as document analysis , is a systematic procedure for reviewing or evaluating documents. This method involves a detailed review of the documents to extract themes or patterns relevant to the research topic .

Documents used in this type of analysis can include a wide variety of materials such as text (words) and images that have been recorded without a researcher’s intervention. The domain of document analysis, therefore, includes all kinds of texts – books, newspapers, letters, study reports, diaries, and more, as well as images like maps, photographs, and films.

Documentary analysis provides valuable insight and a unique perspective on the past, contextualizing the present and providing a baseline for future studies. It is also an essential tool in case studies and when direct observation or participant observation is not possible.

The process usually involves several steps:

• Sourcing : This involves identifying the document or source, its origin, and the context in which it was created.
• Contextualizing : This involves understanding the social, economic, political, and cultural circumstances during the time the document was created.
• Interrogating : This involves asking a series of questions to help understand the document better. For example, who is the author? What is the purpose of the document? Who is the intended audience?
• Making inferences : This involves understanding what the document says (either directly or indirectly) about the topic under study.
• Checking for reliability and validity : Just like other research methods, documentary analysis also involves checking for the validity and reliability of the documents being analyzed.

Documentary Analysis Methods

Documentary analysis as a qualitative research method involves a systematic process. Here are the main steps you would generally follow:

Defining the Research Question

Before you start any research , you need a clear and focused research question . This will guide your decision on what documents you need to analyze and what you’re looking for within them.

Selecting the Documents

Once you know what you’re looking for, you can start to select the relevant documents. These can be a wide range of materials – books, newspapers, letters, official reports, diaries, transcripts of speeches, archival materials, websites, social media posts, and more. They can be primary sources (directly from the time/place/person you are studying) or secondary sources (analyses created by others).

Reading and Interpreting the Documents

You need to closely read the selected documents to identify the themes and patterns that relate to your research question. This might involve content analysis (looking at what is explicitly stated) and discourse analysis (looking at what is implicitly stated or implied). You need to understand the context in which the document was created, the author’s purpose, and the audience’s perspective.

Coding and Categorizing the Data

After the initial reading, the data (text) can be broken down into smaller parts or “codes.” These codes can then be categorized based on their similarities and differences. This process of coding helps in organizing the data and identifying patterns or themes.

Analyzing the Data

Once the data is organized, it can be analyzed to make sense of it. This can involve comparing the data with existing theories, examining relationships between categories, or explaining the data in relation to the research question.

Validating the Findings

The researcher needs to ensure that the findings are accurate and credible. This might involve triangulating the data (comparing it with other sources or types of data), considering alternative explanations, or seeking feedback from others.

Reporting the Findings

The final step is to report the findings in a clear, structured way. This should include a description of the methods used, the findings, and the researcher’s interpretations and conclusions.

Applications of Documentary Analysis

Documentary analysis is widely used across a variety of fields and disciplines due to its flexible and comprehensive nature. Here are some specific applications:

Historical Research

Documentary analysis is a fundamental method in historical research. Historians use documents to reconstruct past events, understand historical contexts, and interpret the motivations and actions of historical figures. Documents analyzed may include personal letters, diaries, official records, newspaper articles, photographs, and more.

Social Science Research

Sociologists, anthropologists, and political scientists use documentary analysis to understand social phenomena, cultural practices, political events, and more. This might involve analyzing government policies, organizational records, media reports, social media posts, and other documents.

Legal Research

In law, documentary analysis is used in case analysis and statutory interpretation. Legal practitioners and scholars analyze court decisions, statutes, regulations, and other legal documents.

Business and Market Research

Companies often analyze documents to gather business intelligence, understand market trends, and make strategic decisions. This might involve analyzing competitor reports, industry news, market research studies, and more.

Media and Communication Studies

Scholars in these fields might analyze media content (e.g., news reports, advertisements, social media posts) to understand media narratives, public opinion, and communication practices.

Literary and Film Studies

In these fields, the “documents” might be novels, poems, films, or scripts. Scholars analyze these texts to interpret their meaning, understand their cultural context, and critique their form and content.

Educational Research

Educational researchers may analyze curricula, textbooks, lesson plans, and other educational documents to understand educational practices and policies.

Health Research

Health researchers may analyze medical records, health policies, clinical guidelines, and other documents to study health behaviors, healthcare delivery, and health outcomes.

Examples of Documentary Analysis

Some Examples of Documentary Analysis might be:

• Example 1 : A historian studying the causes of World War I might analyze diplomatic correspondence, government records, newspaper articles, and personal diaries from the period leading up to the war.
• Example 2 : A policy analyst trying to understand the impact of a new public health policy might analyze the policy document itself, as well as related government reports, statements from public health officials, and news media coverage of the policy.
• Example 3 : A market researcher studying consumer trends might analyze social media posts, customer reviews, industry reports, and news articles related to the market they’re studying.
• Example 4 : An education researcher might analyze curriculum documents, textbooks, and lesson plans to understand how a particular subject is being taught in schools. They might also analyze policy documents to understand the broader educational policy context.
• Example 5 : A criminologist studying hate crimes might analyze police reports, court records, news reports, and social media posts to understand patterns in hate crimes, as well as societal and institutional responses to them.
• Example 6 : A journalist writing a feature article on homelessness might analyze government reports on homelessness, policy documents related to housing and social services, news articles on homelessness, and social media posts from people experiencing homelessness.
• Example 7 : A literary critic studying a particular author might analyze their novels, letters, interviews, and reviews of their work to gain insight into their themes, writing style, influences, and reception.

When to use Documentary Analysis

Documentary analysis can be used in a variety of research contexts, including but not limited to:

• When direct access to research subjects is limited : If you are unable to conduct interviews or observations due to geographical, logistical, or ethical constraints, documentary analysis can provide an alternative source of data.
• When studying the past : Documents can provide a valuable window into historical events, cultures, and perspectives. This is particularly useful when the people involved in these events are no longer available for interviews or when physical evidence is lacking.
• When corroborating other sources of data : If you have collected data through interviews, surveys, or observations, analyzing documents can provide additional evidence to support or challenge your findings. This process of triangulation can enhance the validity of your research.
• When seeking to understand the context : Documents can provide background information that helps situate your research within a broader social, cultural, historical, or institutional context. This can be important for interpreting your other data and for making your research relevant to a wider audience.
• When the documents are the focus of the research : In some cases, the documents themselves might be the subject of your research. For example, you might be studying how a particular topic is represented in the media, how an author’s work has evolved over time, or how a government policy was developed.
• When resources are limited : Compared to methods like experiments or large-scale surveys, documentary analysis can often be conducted with relatively limited resources. It can be a particularly useful method for students, independent researchers, and others who are working with tight budgets.
• When providing an audit trail for future researchers : Documents provide a record of events, decisions, or conditions at specific points in time. They can serve as an audit trail for future researchers who want to understand the circumstances surrounding a particular event or period.

Purpose of Documentary Analysis

The purpose of documentary analysis in research can be multifold. Here are some key reasons why a researcher might choose to use this method:

• Understanding Context : Documents can provide rich contextual information about the period, environment, or culture under investigation. This can be especially useful for historical research, where the context is often key to understanding the events or trends being studied.
• Direct Source of Data : Documents can serve as primary sources of data. For instance, a letter from a historical figure can give unique insights into their thoughts, feelings, and motivations. A company’s annual report can offer firsthand information about its performance and strategy.
• Corroboration and Verification : Documentary analysis can be used to validate and cross-verify findings derived from other research methods. For example, if interviews suggest a particular outcome, relevant documents can be reviewed to confirm the accuracy of this finding.
• Substituting for Other Methods : When access to the field or subjects is not possible due to various constraints (geographical, logistical, or ethical), documentary analysis can serve as an alternative to methods like observation or interviews.
• Unobtrusive Method : Unlike some other research methods, documentary analysis doesn’t require interaction with subjects, and therefore doesn’t risk altering the behavior of those subjects.
• Longitudinal Analysis : Documents can be used to study change over time. For example, a researcher might analyze census data from multiple decades to study demographic changes.
• Providing Rich, Qualitative Data : Documents often provide qualitative data that can help researchers understand complex issues in depth. For example, a policy document might reveal not just the details of the policy, but also the underlying beliefs and attitudes that shaped it.

Advantages of Documentary Analysis

Documentary analysis offers several advantages as a research method:

• Unobtrusive : As a non-reactive method, documentary analysis does not require direct interaction with human subjects, which means that the research doesn’t affect or influence the subjects’ behavior.
• Rich Historical and Contextual Data : Documents can provide a wealth of historical and contextual information. They allow researchers to examine events and perspectives from the past, even from periods long before modern research methods were established.
• Efficiency and Accessibility : Many documents are readily accessible, especially with the proliferation of digital archives and databases. This accessibility can often make documentary analysis a more efficient method than others that require data collection from human subjects.
• Cost-Effective : Compared to other methods, documentary analysis can be relatively inexpensive. It generally requires fewer resources than conducting experiments, surveys, or fieldwork.
• Permanent Record : Documents provide a permanent record that can be reviewed multiple times. This allows for repeated analysis and verification of the data.
• Versatility : A wide variety of documents can be analyzed, from historical texts to contemporary digital content, providing flexibility and applicability to a broad range of research questions and fields.
• Ability to Cross-Verify (Triangulate) Data : Documentary analysis can be used alongside other methods as a means of triangulating data, thus adding validity and reliability to the research.

Limitations of Documentary Analysis

While documentary analysis offers several benefits as a research method, it also has its limitations. It’s important to keep these in mind when deciding to use documentary analysis and when interpreting your findings:

• Authenticity : Not all documents are genuine, and sometimes it can be challenging to verify the authenticity of a document, particularly for historical research.
• Bias and Subjectivity : All documents are products of their time and their authors. They may reflect personal, cultural, political, or institutional biases, and these biases can affect the information they contain and how it is presented.
• Incomplete or Missing Information : Documents may not provide all the information you need for your research. There may be gaps in the record, or crucial information may have been omitted, intentionally or unintentionally.
• Access and Availability : Not all documents are readily available for analysis. Some may be restricted due to privacy, confidentiality, or security considerations. Others may be difficult to locate or access, particularly historical documents that haven’t been digitized.
• Interpretation : Interpreting documents, particularly historical ones, can be challenging. You need to understand the context in which the document was created, including the social, cultural, political, and personal factors that might have influenced its content.
• Time-Consuming : While documentary analysis can be cost-effective, it can also be time-consuming, especially if you have a large number of documents to analyze or if the documents are lengthy or complex.
• Lack of Control Over Data : Unlike methods where the researcher collects the data themselves (e.g., through experiments or surveys), with documentary analysis, you have no control over what data is available. You are reliant on what others have chosen to record and preserve.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Here's What You Need to Understand About Research Methodology

Table of Contents

Research methodology involves a systematic and well-structured approach to conducting scholarly or scientific inquiries. Knowing the significance of research methodology and its different components is crucial as it serves as the basis for any study.

Typically, your research topic will start as a broad idea you want to investigate more thoroughly. Once you’ve identified a research problem and created research questions , you must choose the appropriate methodology and frameworks to address those questions effectively.

What is the definition of a research methodology?

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

The methods section should give a description of the process that will convert your idea into a study. Additionally, the outcomes of your process must provide valid and reliable results resonant with the aims and objectives of your research. This thumb rule holds complete validity, no matter whether your paper has inclinations for qualitative or quantitative usage.

Studying research methods used in related studies can provide helpful insights and direction for your own research. Now easily discover papers related to your topic on SciSpace and utilize our AI research assistant, Copilot , to quickly review the methodologies applied in different papers.

The need for a good research methodology

While deciding on your approach towards your research, the reason or factors you weighed in choosing a particular problem and formulating a research topic need to be validated and explained. A research methodology helps you do exactly that. Moreover, a good research methodology lets you build your argument to validate your research work performed through various data collection methods, analytical methods, and other essential points.

Just imagine it as a strategy documented to provide an overview of what you intend to do.

While undertaking any research writing or performing the research itself, you may get drifted in not something of much importance. In such a case, a research methodology helps you to get back to your outlined work methodology.

A research methodology helps in keeping you accountable for your work. Additionally, it can help you evaluate whether your work is in sync with your original aims and objectives or not. Besides, a good research methodology enables you to navigate your research process smoothly and swiftly while providing effective planning to achieve your desired results.

What is the basic structure of a research methodology?

Usually, you must ensure to include the following stated aspects while deciding over the basic structure of your research methodology:

1. Your research procedure

Explain what research methods you’re going to use. Whether you intend to proceed with quantitative or qualitative, or a composite of both approaches, you need to state that explicitly. The option among the three depends on your research’s aim, objectives, and scope.

2. Provide the rationality behind your chosen approach

Based on logic and reason, let your readers know why you have chosen said research methodologies. Additionally, you have to build strong arguments supporting why your chosen research method is the best way to achieve the desired outcome.

3. Explain your mechanism

The mechanism encompasses the research methods or instruments you will use to develop your research methodology. It usually refers to your data collection methods. You can use interviews, surveys, physical questionnaires, etc., of the many available mechanisms as research methodology instruments. The data collection method is determined by the type of research and whether the data is quantitative data(includes numerical data) or qualitative data (perception, morale, etc.) Moreover, you need to put logical reasoning behind choosing a particular instrument.

4. Significance of outcomes

The results will be available once you have finished experimenting. However, you should also explain how you plan to use the data to interpret the findings. This section also aids in understanding the problem from within, breaking it down into pieces, and viewing the research problem from various perspectives.

5. Reader’s advice

Anything that you feel must be explained to spread more awareness among readers and focus groups must be included and described in detail. You should not just specify your research methodology on the assumption that a reader is aware of the topic.  

All the relevant information that explains and simplifies your research paper must be included in the methodology section. If you are conducting your research in a non-traditional manner, give a logical justification and list its benefits.

6. Explain your sample space

Include information about the sample and sample space in the methodology section. The term "sample" refers to a smaller set of data that a researcher selects or chooses from a larger group of people or focus groups using a predetermined selection method. Let your readers know how you are going to distinguish between relevant and non-relevant samples. How you figured out those exact numbers to back your research methodology, i.e. the sample spacing of instruments, must be discussed thoroughly.

For example, if you are going to conduct a survey or interview, then by what procedure will you select the interviewees (or sample size in case of surveys), and how exactly will the interview or survey be conducted.

7. Challenges and limitations

This part, which is frequently assumed to be unnecessary, is actually very important. The challenges and limitations that your chosen strategy inherently possesses must be specified while you are conducting different types of research.

The importance of a good research methodology

You must have observed that all research papers, dissertations, or theses carry a chapter entirely dedicated to research methodology. This section helps maintain your credibility as a better interpreter of results rather than a manipulator.

A good research methodology always explains the procedure, data collection methods and techniques, aim, and scope of the research. In a research study, it leads to a well-organized, rationality-based approach, while the paper lacking it is often observed as messy or disorganized.

You should pay special attention to validating your chosen way towards the research methodology. This becomes extremely important in case you select an unconventional or a distinct method of execution.

Curating and developing a strong, effective research methodology can assist you in addressing a variety of situations, such as:

• When someone tries to duplicate or expand upon your research after few years.
• If a contradiction or conflict of facts occurs at a later time. This gives you the security you need to deal with these contradictions while still being able to defend your approach.
• Gaining a tactical approach in getting your research completed in time. Just ensure you are using the right approach while drafting your research methodology, and it can help you achieve your desired outcomes. Additionally, it provides a better explanation and understanding of the research question itself.
• Documenting the results so that the final outcome of the research stays as you intended it to be while starting.

Instruments you could use while writing a good research methodology

As a researcher, you must choose which tools or data collection methods that fit best in terms of the relevance of your research. This decision has to be wise.

There exists many research equipments or tools that you can use to carry out your research process. These are classified as:

a. Interviews (One-on-One or a Group)

An interview aimed to get your desired research outcomes can be undertaken in many different ways. For example, you can design your interview as structured, semi-structured, or unstructured. What sets them apart is the degree of formality in the questions. On the other hand, in a group interview, your aim should be to collect more opinions and group perceptions from the focus groups on a certain topic rather than looking out for some formal answers.

In surveys, you are in better control if you specifically draft the questions you seek the response for. For example, you may choose to include free-style questions that can be answered descriptively, or you may provide a multiple-choice type response for questions. Besides, you can also opt to choose both ways, deciding what suits your research process and purpose better.

c. Sample Groups

Similar to the group interviews, here, you can select a group of individuals and assign them a topic to discuss or freely express their opinions over that. You can simultaneously note down the answers and later draft them appropriately, deciding on the relevance of every response.

d. Observations

If your research domain is humanities or sociology, observations are the best-proven method to draw your research methodology. Of course, you can always include studying the spontaneous response of the participants towards a situation or conducting the same but in a more structured manner. A structured observation means putting the participants in a situation at a previously decided time and then studying their responses.

Of all the tools described above, it is you who should wisely choose the instruments and decide what’s the best fit for your research. You must not restrict yourself from multiple methods or a combination of a few instruments if appropriate in drafting a good research methodology.

Types of research methodology

A research methodology exists in various forms. Depending upon their approach, whether centered around words, numbers, or both, methodologies are distinguished as qualitative, quantitative, or an amalgamation of both.

1. Qualitative research methodology

When a research methodology primarily focuses on words and textual data, then it is generally referred to as qualitative research methodology. This type is usually preferred among researchers when the aim and scope of the research are mainly theoretical and explanatory.

The instruments used are observations, interviews, and sample groups. You can use this methodology if you are trying to study human behavior or response in some situations. Generally, qualitative research methodology is widely used in sociology, psychology, and other related domains.

2. Quantitative research methodology

If your research is majorly centered on data, figures, and stats, then analyzing these numerical data is often referred to as quantitative research methodology. You can use quantitative research methodology if your research requires you to validate or justify the obtained results.

In quantitative methods, surveys, tests, experiments, and evaluations of current databases can be advantageously used as instruments If your research involves testing some hypothesis, then use this methodology.

3. Amalgam methodology

As the name suggests, the amalgam methodology uses both quantitative and qualitative approaches. This methodology is used when a part of the research requires you to verify the facts and figures, whereas the other part demands you to discover the theoretical and explanatory nature of the research question.

The instruments for the amalgam methodology require you to conduct interviews and surveys, including tests and experiments. The outcome of this methodology can be insightful and valuable as it provides precise test results in line with theoretical explanations and reasoning.

The amalgam method, makes your work both factual and rational at the same time.

Final words: How to decide which is the best research methodology?

If you have kept your sincerity and awareness intact with the aims and scope of research well enough, you must have got an idea of which research methodology suits your work best.

Before deciding which research methodology answers your research question, you must invest significant time in reading and doing your homework for that. Taking references that yield relevant results should be your first approach to establishing a research methodology.

Moreover, you should never refrain from exploring other options. Before setting your work in stone, you must try all the available options as it explains why the choice of research methodology that you finally make is more appropriate than the other available options.

You should always go for a quantitative research methodology if your research requires gathering large amounts of data, figures, and statistics. This research methodology will provide you with results if your research paper involves the validation of some hypothesis.

Whereas, if  you are looking for more explanations, reasons, opinions, and public perceptions around a theory, you must use qualitative research methodology.The choice of an appropriate research methodology ultimately depends on what you want to achieve through your research.

Frequently Asked Questions (FAQs) about Research Methodology

1. how to write a research methodology.

You can always provide a separate section for research methodology where you should specify details about the methods and instruments used during the research, discussions on result analysis, including insights into the background information, and conveying the research limitations.

2. What are the types of research methodology?

There generally exists four types of research methodology i.e.

• Observation
• Experimental
• Derivational

3. What is the true meaning of research methodology?

The set of techniques or procedures followed to discover and analyze the information gathered to validate or justify a research outcome is generally called Research Methodology.

4. Where lies the importance of research methodology?

Your research methodology directly reflects the validity of your research outcomes and how well-informed your research work is. Moreover, it can help future researchers cite or refer to your research if they plan to use a similar research methodology.

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Documentation in Reports and Research Papers

• An Introduction to Punctuation
• Ph.D., Rhetoric and English, University of Georgia
• M.A., Modern English and American Literature, University of Leicester
• B.A., English, State University of New York

In a report or  research paper , documentation is the evidence  provided for information and ideas borrowed from others. That evidence includes both primary sources  and secondary sources .

There are numerous documentation styles and formats, including MLA style (used for research in the humanities), APA style (psychology, sociology, education), Chicago style (history), and ACS style (chemistry).

Examples and Observations

• Adrienne Escoe "Documentation has many meanings, from the broad—anything written in any medium—to the narrow—policies and procedures manuals or perhaps records." ( T he Practical Guide to People-Friendly Documentation , 2nd. ed. ASQ Quality Press, 2001)
• Kristin R. Woolever "An issue more important than documentation form is knowing when to document. In brief, anything that is copied needs to be documented... "Perhaps the best tip for knowing when to document is to use common sense. If writers are careful to give credit where it is due and to provide the reader with easy access to all the source material, the text is probably documented appropriately." ( About Writing: A Rhetoric for Advanced Writers . Wadsworth, 1991)

Note-Taking and Documentation During the Research Process

• Linda Smoak Schwartz "The most important thing to remember when you take notes from your sources is that you must clearly distinguish between quoted, paraphrased , and summarized material that must be documented in your paper and ideas that do not require documentation because they are considered general knowledge about that subject." ( The Wadsworth Guide to MLA Documentation , 2nd ed. Wadsworth, 2011)

Library Resources Versus Internet Resources

• Susan K. Miller-Cochran and Rochelle L. Rodrigo "When you are reviewing and analyzing your resources, keep in mind that the library/Internet distinction is not quite as simple as it might seem at first. The Internet is where students often turn when they are having difficulty getting started. Many instructors warn students against using Internet resources because they are easily alterable and because anyone can construct and publish a Web site. These points are important to remember, but it is essential to use clear evaluative criteria when you are looking at any resource. Print resources can be self-published as well. Analyzing how easily a resource is changed, how often it is changed, who changed it, who reviews it, and who is responsible for the content will help you choose resources that are reliable and credible, wherever you might find them." ( The Wadsworth Guide to Research, Documentation , rev. ed. Wadsworth, 2011)

Parenthetical Documentation

• Joseph F. Trimmer "You may decide to vary the pattern of documentation by presenting the information from a source and placing the author's name and page number in parentheses at the end of the sentence. This method is particularly useful if you have already established the identity of your source in a previous sentence and now want to develop the author's idea in some detail without having to clutter your sentences with constant references to his or her name.​" ( A Guide to MLA Documentation , 9th ed. Wadsworth, 2012)
• What Is a Style Guide and Which One Do You Need?
• Bibliography: Definition and Examples
• Definition of Appendix in a Book or Written Work
• Characteristics of a Formal Prose Style
• What Is a Research Paper?
• Primary and Secondary Sources in History
• Thesis: Definition and Examples in Composition
• Justification (Typesetting and Composition)
• What Is a Primary Source?
• How to Use Footnotes in Research Papers
• An Introduction to Academic Writing
• Biographies: The Stories of Humanity
• Margin (Composition Format) Definition
• Holistic Grading (Composition)
• Definition and Examples of Evidence in Argument
• How to Use Block Quotations in Writing

Research Methodologies Guide

• Action Research
• Bibliometrics
• Case Studies
• Content Analysis
• Digital Scholarship This link opens in a new window
• Documentary
• Ethnography
• Focus Groups
• Grounded Theory
• Life Histories/Autobiographies
• Longitudinal
• Participant Observation
• Qualitative Research (General)
• Quasi-Experimental Design
• Usability Studies

Documentary Research

According to Scott & Marshall (2015), Documentary Research is

" Research that uses personal and official documents as a source material. Documents... may include such things as newspapers, diaries, stamps, directories, handbills, maps, government statistical publications, photographs, paintings, gramophone records, tapes, and computer files. "

Documentary research is often conducted by social scientists to assess a set of documents for historical or social value, or to create a larger narrative through the study of multiple documents surrounding an event or individual. 

Documentary research is often related to Content Analysis research methodologies. 

For more information, browse the selected resources below:

Books and articles

• Documentary Research in the Social Sciences by Malcolm Tight Publication Date: 2019 From diaries and letters to surveys and interview transcripts, documents are a cornerstone of social science research. This book guides you through the documentary research process, from choosing the best research design, through data collection and analysis, to publishing and sharing research findings.
• Documentary Research by Gary McCulloch Publication Date: 2004 Documentary sources have become increasingly neglected in education and the social sciences. This book seeks to emphasise their potential value and importance for an understanding of modern societies, while also recognising their limitations, and explores their relationship with other research strategies.
• An Introduction to Documentary Research A brief introduction to documentary research from the American Educational Research Association.
• Documentary Research [Reference] An encyclopedia entry on Documentary Research from the Encyclopedia of Curriculum Studies.
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• Next: Ethnography >>
• Last Updated: Sep 11, 2024 11:05 AM
• URL: https://instr.iastate.libguides.com/researchmethods

Research Methodology in Education

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March 9, 2016

• An Introduction to Document Analysis

Introduction

Document analysis is a form of qualitative research in which documents are interpreted by the researcher to give voice and meaning around an assessment topic (Bowen, 2009). Analyzing documents incorporates coding content into themes similar to how focus group or interview transcripts are analyzed (Bowen,2009). A rubric can also be used to grade or score document. There are three primary types of documents (O’Leary, 2014):

• Public Records: The official, ongoing records of an organization’s activities. Examples include student transcripts, mission statements, annual reports, policy manuals, student handbooks, strategic plans, and syllabi.
• Personal Documents: First-person accounts of an individual’s actions, experiences, and beliefs. Examples include calendars, e-mails, scrapbooks, blogs, Facebook posts, duty logs, incident reports, reflections/journals, and newspapers.
• Physical Evidence: Physical objects found within the study setting (often called artifacts). Examples include flyers, posters, agendas, handbooks, and training materials.

Document analysis is a social research method and is an important research tool in its own right, and is an invaluable part of most schemes of triangulation, the combination of methodologies in the study of the same phenomenon (Bowen, 2009). In order to seek convergence and corroboration, qualitative researchers usually use at least two resources through using different data sources and methods. The purpose of triangulating is to provide a confluence of evidence that breeds credibility (Bowen, 2009). Corroborating findings across data sets can reduce the impact of potential bias by examining information collected through different methods. Also, combining qualitative and quantitative sometimes included in document analysis called mixed-methods studies.  

Before actual document analysis takes place, the researcher must go through a detailed planning process in order to ensure reliable results. O’Leary outlines an 8-step planning process that should take place not just in document analysis, but all textual analysis (2014):

• Create a list of texts to explore (e.g., population, samples, respondents, participants).
• Consider how texts will be accessed with attention to linguistic or cultural barriers.
• Acknowledge and address biases.
• Develop appropriate skills for research.
• Consider strategies for ensuring credibility.
• Know the data one is searching for.
• Consider ethical issues (e.g., confidential documents).
• Have a backup plan.

A researcher can use a huge plethora of texts for research, although by far the most common is likely to be the use of written documents (O’Leary, 2014). There is the question of how many documents the researcher should gather. Bowen suggests that a wide array of documents is better, although the question should be more about quality of the document rather than quantity (Bowen, 2009). O’Leary also introduces two major issues to consider when beginning document analysis. The first is the issue of bias, both in the author or creator of the document, and the researcher as well (2014). The researcher must consider the subjectivity of the author and also the personal biases he or she may be bringing to the research. Bowen adds that the researcher must evaluate the original purpose of the document, such as the target audience (2009). He or she should also consider whether the author was a firsthand witness or used secondhand sources. Also important is determining whether the document was solicited, edited, and/or anonymous (Bowen, 2009). O’Leary’s second major issue is the “unwitting” evidence, or latent content, of the document. Latent content refers to the style, tone, agenda, facts or opinions that exist in the document. This is a key first step that the researcher must keep in mind (O’Leary, 2014). Bowen adds that documents should be assessed for their completeness; in other words, how selective or comprehensive their data is (2009). Also of paramount importance when evaluating documents is not to consider the data as “necessarily precise, accurate, or complete recordings of events that have occurred” (Bowen, 2009, p. 33). These issues are summed up in another eight-step process offered by O’Leary (2014):

• Gather relevant texts.
• Develop an organization and management scheme.
• Make copies of the originals for annotation.
• Asses authenticity of documents.
• Explore document’s agenda, biases.
• Explore background information (e.g., tone, style, purpose).
• Ask questions about document (e.g., Who produced it? Why? When? Type of data?).
• Explore content.

Step eight refers to the process of exploring the “witting” evidence, or the actual content of the documents, and O’Leary gives two major techniques for accomplishing this (2014). One is the interview technique. In this case, the researcher treats the document like a respondent or informant that provides the researcher with relevant information (O’Leary, 2014). The researcher “asks” questions then highlights the answer within the text. The other technique is noting occurrences, or content analysis, where the researcher quantifies the use of particular words, phrases and concepts (O’Leary, 2014). Essentially, the researcher determines what is being searched for, then documents and organizes the frequency and amount of occurrences within the document. The information is then organized into what is “related to central questions of the research” (Bowen, 2009, p. 32). Bowen notes that some experts object to this kind of analysis, saying that it obscures the interpretive process in the case of interview transcriptions (Bowen, 2009). However, Bowen reminds us that documents include a wide variety of types, and content analysis can be very useful for painting a broad, overall picture (2009). According to Bowen (2009), content analysis, then, is used as a “first-pass document review” (p. 32) that can provide the researcher a means of identifying meaningful and relevant passages.

In addition to content analysis, Bowen also notes thematic analysis, which can be considered a form of pattern recognition with the document’s data (2009). This analysis takes emerging themes and makes them into categories used for further analysis, making it a useful practice for grounded theory. It includes careful, focused reading and re-reading of data, as well as coding and category construction (Bowen, 2009). The emerging codes and themes may also serve to “integrate data gathered by different methods” (Bowen, 2009, p. 32). Bowen sums up the overall concept of document analysis as a process of “evaluating documents in such a way that empirical knowledge is produced and understanding is developed” (2009, p. 33). It is not just a process of lining up a collection of excerpts that convey whatever the researcher desires. The researcher must maintain a high level of objectivity and sensitivity in order for the document analysis results to be credible and valid (Bowen, 2009).

The Advantages of Document Analysis

There are many reasons why researchers choose to use document analysis. Firstly, document analysis is an efficient and effective way of gathering data because documents are manageable and practical resources. Documents are commonplace and come in a variety of forms, making documents a very accessible and reliable source of data. Obtaining and analysing documents is often far more cost efficient and time efficient than conducting your own research or experiments (Bowen, 2009). Also, documents are stable, “non-reactive” data sources, meaning that they can be read and reviewed multiple times and remain unchanged by the researcher’s influence or research process (Bowen, 2009, p. 31).

Document analysis is often used because of the many different ways it can support and strengthen research. Document analysis can be used in many different fields of research, as either a primary method of data collection or as a compliment to other methods. Documents can provide supplementary research data, making document analysis a useful and beneficial method for most research. Documents can provide background information and broad coverage of data, and are therefore helpful in contextualizing one’s research within its subject or field (Bowen, 2009). Documents can also contain data that no longer can be observed, provide details that informants have forgotten, and can track change and development. Document analysis can also point to questions that need to be asked or to situations that need to be observed, making the use of document analysis a way to ensure your research is critical and comprehensive (Bowen, 2009).

Concerns to Keep in Mind When Using Document Analysis

The disadvantages of using document analysis are not so much limitations as they are potential concerns to be aware of before choosing the method or when using it. An initial concern to consider is that documents are not created with data research agendas and therefore require some investigative skills. A document will not perfectly provide all of the necessary information required to answer your research questions. Some documents may only provide a small amount of useful data or sometimes none at all. Other documents may be incomplete, or their data may be inaccurate or inconsistent. Sometimes there are gaps or sparseness of documents, leading to more searching or reliance on additional documents then planned (Bowen, 2009). Also, some documents may not be available or easily accessible. For these reasons, it is important to evaluate the quality of your documents and to be prepared to encounter some challenges or gaps when employing document analysis.

Another concern to be aware of before beginning document analysis, and to keep in mind during, is the potential presence of biases, both in a document and from the researcher. Both Bowen and O’Leary state that it is important to thoroughly evaluate and investigate the subjectivity of documents and your understanding of their data in order to preserve the credibility of your research (2009; 2014).

The reason that the issues surrounding document analysis are concerns and not disadvantages is that they can be easily avoided by having a clear process that incorporates evaluative steps and measures, as previously mentioned above and exemplified by O’Leary’s two eight-step processes. As long as a researcher begins document analysis knowing what the method entails and has a clear process planned, the advantages of document analysis are likely to far outweigh the amount of issues that may arise.

References:

Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27-40. doi:10.3316/QRJ0902027 O’Leary, Z. (2014). The essential guide to doing your research project (2nd ed.). Thousand Oaks, CA: SAGE Publications, Inc.

And So It Was Written

Author: Triad 3

Published: March 9, 2016

Word Count: 1626

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I found the document so interesting. Thank you

Dear Triad Your article was very insightful. I am currently researching about document analysis to make it my methodology strategy to analyze a web application. I would be glad if you had any more material regarding this subject to share.

Very helpful.

Thank you for this valuable information. I request for more such information in qualitative analysis.

I benefited from this article so much . thank you for taking your time to write and share it.

This is really helpful for understanding the basic concept of document analysis. Really impressive!

This is one of the good way to remove difficulties during writing the research

Hi, valuable information herein. My research is qualitative and I want to take a number of pictures which I will then use to formulate questions for the interview guide. My question is this, how do I formulate the document analysis checklist?

Regards, Nancy

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The Impact of Structured and Standardized Documentation on Documentation Quality; a Multicenter, Retrospective Study

1 Department of Otorhinolaryngology and Head and Neck Surgery, Radboud University Medical Center, Nijmegen, Netherlands

Rudolf B. Kool

3 Radboud University Medical Center, Radboud Institute for Health Sciences, IQ Healthcare, Nijmegen, Netherlands

Ludi E. Smeele

2 Department of Head and Neck Oncology and Surgery, Antoni Van Leeuwenhoek, Amsterdam, Netherlands

Richard Dirven

Chrisje a. den besten, luc h. e. karssemakers, tim verhoeven.

4 Department of Oromaxillofacial Surgery and Head and Neck Surgery, Radboud University Medical Center, Nijmegen, Netherlands

Jasmijn M. Herruer

Guido b. van den broek, robert p. takes, associated data.

Data is available upon reasonable request.

The reuse of healthcare data for various purposes will become increasingly important in the future. To enable the reuse of clinical data, structured and standardized documentation is conditional. However, the primary purpose of clinical documentation is to support high-quality patient care. Therefore, this study investigated the effect of increased structured and standardized documentation on the quality of notes in the Electronic Health Record. A multicenter, retrospective design was used to assess the difference in note quality between 144 unstructured and 144 structured notes. Independent reviewers measured note quality by scoring the notes with the Qnote instrument. This instrument rates all note elements independently using and results in a grand mean score on a 0–100 scale. The mean quality score for unstructured notes was 64.35 (95% CI 61.30–67.35). Structured and standardized documentation improved the Qnote quality score to 77.2 (95% CI 74.18–80.21), a 12.8 point difference (p < 0.001). Furthermore, results showed that structured notes were significantly longer than unstructured notes. Nevertheless, structured notes were more clear and concise. Structured documentation led to a significant increase in note quality. Moreover, considering the benefits of structured data recording in terms of data reuse, implementing structured and standardized documentation into the EHR is recommended.

Supplementary information

The online version contains supplementary material available at 10.1007/s10916-022-01837-9.

Introduction

Clinical documentation is the process of creating a text record that summarizes the interaction between patients and healthcare providers during clinical encounters [ 1 ]. The quality of clinical documentation is important as it impacts quality of patient care, patient safety, and the number of medical errors [ 2 – 4 ]. Furthermore, clinical documentation is increasingly used for other purposes, such as quality measurement, finance, and research. Additionally, regulatory requirements regarding documentation have increased [ 5 , 6 ]. Consequently, physicians are spending more and more time on documentation [ 7 ].

In recent years, various tools and techniques have been developed to increase documentation efficiency and decrease the time physicians need to spend on documentation. These techniques are known as content importing technology (CIT). Examples of CIT are copy and paste functions (CPF), automated data import from other parts of the electronic health record (EHR), templates, or macros. These tools seem to have multiple benefits, primarily faster documentation during patient visits. However, Weis and Levy described that the use of CIT has multiple risks. Incorrect insertion of data from other parts of the record, or excessively long, bloated notes can distract a reader from key, essential facts and data [ 8 ]. However, when used correctly, it should be possible to limit these risks.

In addition to the need to increase documentation efficiency, documentation needs to be accurate. Cohen et al. stated that variation in EHR documentation between physicians impedes effective and safe use of EHRs, emphasizing the need for increased standardization of documentation [ 9 ]. However, some studies have suggested that structured and standardized documentation (hereafter: structured documentation) can impede expressivity in notes. Rosenbloom explored this tension between flexible, narrative documentation and structured documentation and recommended that healthcare providers can choose how to document patient care based on workflow and note content needs [ 1 ]. This implies that structured documentation is preferred when reuse of data is desirable. On the other hand, narrative documentation can be used when reuse of information is not required.

Research has shown that structured documentation can improve provider efficiency and decrease documentation time [ 10 ]. Unfortunately, little is known about the effects that a transition from primarily unstructured, free-text EHR documentation to structured and standardized EHR documentation has on the quality of EHR notes. To date, research on this topic has mainly focused on the difference between paper-based and electronic documentation [ 11 – 13 ]. Although reuse of data, for which structured documentation is essential, will become increasingly important, the primary goal of EHR documentation is supporting high-quality patient care [ 14 ]. Therefore, the primary objective was to investigate the effect of increased standardized and structured documentation on the quality of EHR notes.

Since 2009, the Radboudumc Center for Head and Neck Oncology developed and implemented a highly structured care pathway. A care pathway is a complex intervention for the mutual decision-making and organization of care processes for a well-defined group of patients during a well-defined period [ 15 ]. In 2017, for all stages of the care pathway (e.g. first visit consultation, multidisciplinary tumor board, diagnostic results consultation, treatment, follow-up consultation) the patient information that had to be entered into the EHR was defined. Structured and standardized forms using different types of CIT, automated documentation and standardized response options were developed in Epic EHR (EPIC, Verona Wisconsin). These forms allowed physicians to enter all patient information efficiently into the EHR. This resulted in structured and standardized notes while simultaneously storing structured data elements into the EHR database. These data elements can be reused in other stages of the care pathway, automatically compute referral letters, trigger standardized ordersets, or other tools to make the care process more efficient. Ultimately, this data is used to populate real-time quality dashboards. Furthermore, data can be extracted from the EHR and sent to third parties, such as quality and cancer registries or other health care centers when referring patients. Besides structured data recording, these forms support additional narrative documentation if needed or preferred. Recently, a similar highly structured care pathway with structured documentation based on the previously developed care pathway in Radboudumc, was implemented at the Head and Neck Oncology department in Antoni van Leeuwenhoek. In this center, HiX EHR (Chipsoft, Amsterdam) is used. Because of the difference in EHR vendor and the resulting variation in technical possibilities of the EHRs, there were slight differences in structured forms and notes in both centers. However, the structured forms that were built in center B remain highly similar to the forms used in Center A, as the forms and notes of Center A were shared with center B and were subsequently used in the development phase.

A multicenter, retrospective design was used to assess the difference in note quality in two tertiary HNC care centers. In center A, structured documentation has gradually increased in recent years. Therefore, the EHR notes of patients seen between January and December 2013 were compared with those of patients seen between January and December 2019. The transition to structured documentation in center B was more immediate due to implementing an EHR embedded care path that supports structured documentation. Therefore, the notes of patients seen between March and July 2020 were compared with those seen between January and April 2021. This shorter interval added to internal validity because it is less likely that other, time-related factors influenced the outcome. Notes of consultations of adult patients that completed at least one initial oncological consultation (IOC) or follow-up consultation (FUC) during the study period were eligible for inclusion. In both centers, a list of eligible notes was extracted from the EHR and for each consultation type and each documentation method, 36 notes were randomly drawn. In total, 288 notes were included. Subsequently, notes were carefully anonymized. All names, dates, and other identifying information were replaced with < name > , < date > , or otherwise masked. A translated example of a structured note is available as Electronic Supplementary Material (Online Resource 1 ). HNC care providers from center A were recruited to rate the notes collected in center B, and HNC care providers in center B were recruited to rate notes from center A to minimize bias. Each physician was assigned a random group of notes. However, unstructured and structured notes were evenly distributed among raters. Subsequently, notes were scored in a secured digital environment created in CastorEDC (Castor, Amsterdam), an electronic data capture platform.

The quality of the notes was assessed using the Qnote instrument, a validated measurement method for the quality of clinical documentation [ 16 ]. This instrument rates every element of a note individually, by using one or more of seven components (Table ​ (Table1 1 ).

Elements and components of Qnote instrument

The primary outcomes of this study were the quality of notes and note elements, measured by the Qnote instrument on a 100-point scale. Secondary outcomes included length of notes in words, mean component scores per note, and subjective quality measured by a general score given on a scale of 1–10.

Data were notated and analyzed using SPSS version 25 (IBM Corp, Armonk, NY, USA). Two-way ANOVA was used to assess differences in note quality between before and after implementation of structured documentation. The Qnote grand mean score and element scores were outcome variables. The type of note, the originating center, and a dummy variable indicating the period in which the note was written were added as fixed factors. Two-tailed significance was defined as p < 0.05 or a 95% CI not including zero.

This study was approved by the Institutional Review Boards at Antoni van Leeuwenhoek Netherlands Cancer Institute and Radboud University Medical Center.

The grand mean score of all 144 EHR notes written before implementing structured documentation was 64.35 (95% CI 61.30–67.35). When comparing this score to all 144 EHR notes written with structured documentation, a 12.8 point difference (p < 0.001) was found. Structured documentation improved the grand mean score to 77.2 (95% CI 74.18–80.21). Subsequently, additional analysis was conducted on all element scores. The results are shown in Table ​ Table2 2 .

Estimated marginal means of Qnote scores and main effect of structured documentation

* difference significant (p < 0.05)

Table ​ Table3 3 shows descriptive results of element scores displayed per type of note. What can be observed from the data in Table ​ Table3 3 is that for structured documentation, the standard deviation decreases in most elements scores, indicating the variability in quality seems to be lower in structured notes. Furthermore, when comparing the grand mean score for IOC and FUC notes separately, an increase for both types of notes was found (Fig.  1 ). IOC Qnote score increased by 14.9 (95% CI 11.3–18.5) points from 67.3 to 82.3. FUC Qnote score increased by 10.8 (95% CI 4.6–17.0) from 61.3 to 72.1.

Descriptive results of Qnote element scores, per note type

* grey marked elements were not evaluated for this note because these elements were considered not relevant in this type of consultation

Boxplot of grand mean score per note type

Subsequently, analysis was conducted on data from both centers separately to determine whether structured documentation led to increased quality in both centers. In center B, an increase of 14.59 was found (95% CI 7.22–21.96) in IOC note quality, and a 16.36 point increase (95% CI 8.99–23.73) in FUC note quality was found. A significant improvement in IOC Qnote score by 15.10 (95% CI 8.26–22.10) was observed in center A. The 5.3 point increase in FUC note quality was not statistically significant (95% CI -1.61–12.14).

Analysis of secondary outcome measures showed a significant increase in note length for structured documentation in both note types. IOC notes increased from 442.1 to 639.6 words, with a mean difference of 197.5 (95% CI 146.9–248.1), translating to a 44.7% increase. A significant 53.3% increase was found in FUC notes, increasing with 46.5 words (95% CI 31.7–61.2) from 86.9 to 133.4. To evaluate whether this increase in note length led to unnecessary long notes containing excessive non-essential information, all scores for a given component were averaged. For example, the component concise was used to rate 9 of the 11 elements used to rate a note. The mean of all conciseness scores was calculated to get an overall indication of the conciseness of the note. Table ​ Table4 4 shows the difference in mean component scores. As can be seen from the data in Table ​ Table4, 4 , the mean conciseness score, indicating whether note elements were focused and brief, increased significantly. Furthermore, the mean clearness score, indicating whether note elements were understandable to clinicians, also increased significantly.

Mean component score difference between unstructured and structured documentation

When analyzing the scores of the general instrument that rated the notes on a scale of one to ten, a significant increase in documentation quality was also found. Mean scores increased from 6.83 to 7.52, which was an 0.68 increase (95% CI 0.44–0.94).

The study offers some important insights into the impact of increased structured and standardized documentation on EHR note quality in outpatient care. In this retrospective multicenter study, our results show that structured documentation is associated with higher quality documentation. In summary, our results show a 20.0% increase measured on a 0–100 scale. Furthermore, results showed that structured notes were significantly longer than unstructured notes, but were more concise nevertheless.

This study showed an overall increase in documentation quality after the implementation of structured and standardized recording. In 8 of the 11 elements measured with the Qnote instrument, a significant increase in quality was found. This result may be explained by the fact that relevant elements and items that have to be documented are presented to the health care provider in an intuitive, uniform way. Therefore, clinicians are less likely to forget certain elements and items within the note. Furthermore, repeatedly recording in the same format ensures the physician is trained to record properly and completely. The medication element showed a minor, insignificant increase. This might be because medications were not included in notes in one center and therefore did not contribute to the observed results on this element. Additionally, minor, insignificant increases were found in physical examination and plan of care. This could be explained by the fact that the score for these elements was already high in unstructured documentation.

A recent study found variation in the quality of documentation between healthcare providers [ 9 ]. This variation could lead to inefficient documentation and the risk of patient harm from missed or misinterpreted information. Therefore, reducing this variability may also be considered relevant. The descriptive data on element scores in this study showed a trend indicating that the variation in documentation quality decreases when using structured documentation. However, some elements still showed significant variation. Therefore, implementing solutions that reduce variation in documentation quality between encounters and healthcare providers should be encouraged.

In addition, when the notes were analyzed differentiated by center, a significant increase in the quality of IOC notes was observed. This was also the case for follow-up notes in one of the two centers. This supports the conclusion that structured and standardized recording increases documentation quality, independent of a specific center or EHR vendor.

The results also show notes were longer when structured documentation was used. This could be because structured documentation contributes to including all relevant elements, or because health care providers are more reliant on CIT. CIT can be a problem if it leads to unnecessary, unorganized, or unclear information in a note and distracts the reader from the essential information buried within the note. This is known as note bloat. When considering the results of this study, there is no evidence that the longer notes were the result of note bloat. Firstly, an increase in quality in almost all elements where CIT is mainly used (problem list, past medical history, adverse reaction, social and family history) was observed. Secondly, the analysis on components used to assess the individual elements showed significant increases in clearness and conciseness. Therefore, it is safe to assume that in this study, the longer notes were not associated with note bloat and are most likely the result of more complete, and therefore higher quality, documentation.

The reports in the literature to date have mainly focused on the effect of electronic documentation versus handwritten documentation. Some studies have shown a perceived decrease in quality after implementing EHRs, identifying copy-paste functions (CPF) and note clutter as the main reasons for this quality decrease [ 17 ]. Others claim that EHRs increase note quality compared to manual recording in inpatient and outpatient care [ 11 – 13 , 18 ]. A small number of studies have evaluated semi-structured templates that mainly use free-text documentation, comparing them to traditional templates or fully unstructured free-text notes. A small (n = 36) trial comparing outpatient notes written using a traditional template with an optimized template found mixed results, with no difference in overall quality [ 19 ]. However, the intervention notes were inferior in accuracy and usefulness, although better organized. Another study evaluating a quality improvement project to improve clinical documentation quality found no increase in quality [ 20 ]. A third, larger study did find a significant increase in inpatient documentation quality using a semi-structured template [ 21 ]. The abovementioned studies indicate that further research on this topic is warranted. However, our findings show compelling evidence that structured documentation can improve documentation quality.

This study has several strengths. This is the first study to use a validated measure instrument for outpatient notes to examine the impact of structured and standardized recording on outpatient note quality. Given the rising demand for reuse and exchange of healthcare data, structured and standardized data recording will become increasingly important. This study proves that structured documentation can also improve the quality of EHR notes. Furthermore, the increase in quality was found in two centers with different EHRs. These factors contribute to the generalizability of the results.

Another strength of this study is the method used to assess the quality of the notes. Of the instruments available in the literature that are used to assess the quality of documentation, most focus on the absence of data or only assess the global quality of the note, such as the PDSI-9 [ 22 ]. However, the Qnote instrument is based on a qualitative study in which relevant elements of an outpatient clinical note were identified [ 23 ]. Therefore, it is possible to rate the quality of all note elements independently and subsequently calculate a total score. This structured approach is likely to be more objective than other, more general rating instruments. Besides, rating elements individually benefit from being able to identify specific deficits in note quality. Because of this, improving the quality of clinical EHR notes can be conducted in a more targeted and effective way.

This study also has some limitations. Firstly, the main limitation of the retrospective nature of this study is that a causal relationship between the implementation of structured and standardized documenting cannot be established with certainty. In one center, the interval between the two study periods was several years. Therefore, the influence of other factors cannot be eliminated. In the other center, the interval between study periods is shorter, making it highly likely that implementing the standardized care pathway with structured documentation is the primary reason for the increase in note quality. Moreover, analyzing the data differentiated by center resulted in similar outcomes. Secondly, the Qnote instrument has been validated on a population of diabetic patients and not for oncological patients. However, the elements used are general and not disease- or setting-specific. Moreover, the general score given by the raters in this study showed similar or marginally lower scores than the Qnote instrument. This conclusion was also stated in the initial Qnote validation study [ 16 ]. Lastly, due to the visual similarity of structured and standardized notes, the complete blinding of study notes for raters was impossible. This might have led to an unconscious bias. However, the risk was minimized by recruiting note raters employed at another hospital.

The findings of this study support the assumption that structured documentation positively influences documentation quality. This is an important finding, given that the need for structured documentation will only increase in the near future because structured data is key in enabling the reuse of healthcare data. Data reuse will become increasingly important in health care, for various purposes, such as automated quality measurement, information exchange when referring patients to other health care centers, and less time-consuming data collection methods for scientific research. Furthermore, the use and implementation of decision support tools also require structured recording of healthcare data. The abovementioned applications of data reuse in healthcare can lead to increased efficiency and quality of healthcare. Nevertheless, there could be a concern that as data reuse becomes more important, healthcare providers are required to capture more data while providing care. This, in turn, might lead to an increased administrative burden. This should be avoided, as healthcare providers are unlikely to accept a documentation method that adds a significant burden to their workload [ 24 ]. Efforts should be made to to implement structured documentation methods within EHRs to enable data reuse while reducing the administrative burden. The results of this study raise further questions about the benefits and pitfalls of structured documentation systems, on which future studies should focus. These include the effect of the structured documentation systems on documentation time and effort, how physicians' perceptions regarding the documentation process and the EHR are influenced, and how these factors affect adoption, and how these factors affect adoption. As a result, we have started another study to answer such questions.

This study demonstrated that structured and standardized recording led to an increase in the quality of notes in the EHR. Additionally, a significant increase in note length was found. Moreover, the results showed that the longer notes were also considered more clear and concise. Considering the benefits of structured data recording in terms of data reuse, it is recommended to implement structured and standardized documentation into the EHR.

Below is the link to the electronic supplementary material.

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What Is a Research Methodology? | Steps & Tips

Published on August 25, 2022 by Shona McCombes and Tegan George. Revised on September 5, 2024.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation , or research paper , the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research and your dissertation topic .

It should include:

• The type of research you conducted
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• Any tools or materials you used in the research
• How you mitigated or avoided research biases
• Why you chose these methods
• Your methodology section should generally be written in the past tense . Our grammar checker can help ensure consistency in your writing.
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How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, other interesting articles, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ? How did you prevent bias from affecting your data?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalizable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalized your concepts and measured your variables. Discuss your sampling method or inclusion and exclusion criteria , as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on July 4–8, 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

• Information bias
• Omitted variable bias
• Regression to the mean
• Survivorship bias
• Undercoverage bias
• Sampling bias

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyze?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness store’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

• The Hawthorne effect
• Observer bias
• The placebo effect
• Response bias and Nonresponse bias
• The Pygmalion effect
• Recall bias
• Social desirability bias
• Self-selection bias

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods.

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Next, you should indicate how you processed and analyzed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analyzing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorizing and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviors, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalized beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalizable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles

Methodology

• Cluster sampling
• Stratified sampling
• Thematic analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

In a scientific paper, the methodology always comes after the introduction and before the results , discussion and conclusion . The same basic structure also applies to a thesis, dissertation , or research proposal .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

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Documentary Research: What it is, methodology & free examples

Social scientists often conduct documentary research. Its primary use is to assess various documents in the interest of social or historical value. Researchers also conduct documentary research to study multiple documents surrounding events or individuals.

What is documentary research?

Documentary research is the research conducted through the use of official documents or personal documents as the source of information.

Documents can include anything from the following: 

• Directories
• Government statistical publications
• Gramophone records
• Photographs
• Computer files

The above may not fit the traditional bill of a “document”, but companies can use them towards documentary research since they contain information.

Documentary research is similar to content analysis, which involves studying existing information recorded in media, texts, and physical items. Here, data collection from people is not required to conduct research. Hence, this is a prime example of secondary research.

It is essential to consider the quality of the documents while using it as evidence on social relations and social meanings. Keep in mind that, unlike surveys and research interviews, the records are originally published/generated without keeping the purpose of research in mind. It is good practice to cross-verify documents against other similar documents before reaching a decision.

Documentary research examples

Bellow, we can find a few real-life examples of documentary research applied to companies’ daily events.

1. Social research studies

Although documentary research is not used extensively today, it is the go-to research method to conduct social research studies. For example, Karl Marx and Emile Durkheim used documentary research extensively for their research.

Karl Marx used documents like:

• Her Majesty Inspectors of Factories Reports
• Royal Commission
• Inland Revenue Reports

There’s also a record of his use of reports by the Medical Officer of the Privy Council, reports on children’s employment in factories, the Corn-laws, the Banking Acts, and Census Reports for Wales and England to name a few.

Durkheim, one of the founders of Sociology, wrote a book on suicide, which is recognized as the first modern example of a methodical and consistent use of documents for social research.

2. Archival inquiry

The field of sociology has a popular, longstanding tradition of documentary inquiry. Many historians refer to and rely on primary documents for their research. Historians give historical documents more emphasis while conducting research. Of course, as we evolve, virtual documents like emails will play a significant role in research activities conducted by these researchers.

3. Aesthetic interpretation

Documentary research is not limited to text only. Pictures, paintings, videos, audio files, monuments are also used to conduct research. Documentary researchers use these tools in addition to texts while studying social sciences. The use of these tools adds to the authenticity of the textual research, or may very well point out deviations in the findings.

This deviation suggests that investigators research more to draw accurate conclusions.

Documentary research methodology

Documentary research, if conducted thoroughly, can help develop a hypothesis or prove or disprove an existing theory. This of course depends on the methodology applied and the depth of research conducted. The researcher must conduct his/her own secondary research to analyze the contents before extracting it. They must handle the data scientifically.

Follow this four-step approach to control the quality of the content:

The authenticity of the documents

The credibility of the documents

Representativeness of the documents

The meaning derived from the documents

Let’s take a look at these in detail.

Authenticity implies whether the document’s origin is reliable, is the evidence genuine, are the intentions sincere, and what were the commitments to creating the document. The authenticity of the source is the primary criterion of documentary research.

Credibility means the subjective and objective components that make one believe the source of information and whether the data is free from distortion and error. The information must be trustworthy and must have some level of expertise.

Representativeness refers to whether the document represents a more extensive collection of the data point, and it is an aggregation of the topic being studied. That said, documents get distorted with time due to the inclusion of new factors, and a check has to be made to ensure the documents are representative.

Meaning means whether the findings are understandable and clear to be called evidence. The goal of examining documents is to understand its significance and meaning. Researchers must find out whether the document fits within the historical context or not.

Advantages of documentary study

Here are the advantages of the documentary research method:

• Data readily available: Data is readily available in various sources. You only need to know where to look and how to use it. The data is available in different forms, and harnessing it is the real challenge.
• Inexpensive and economical: The data for research is already collected and published in either print or other forms. The researcher does not need to spend money and time like they do to collect market research insights and gather data. They need to search for and compile the available data from different sources.
• Saves time: Conducting market research is time-consuming. Responses will not come in quickly as expected, and gathering global responses will take a huge amount of time. If you have all the reference documents available (or you know where to find them), research is relatively quick.
• Non-bias: Primary data collection tends to be biased. This bias depends on a lot of factors like the age of the respondents, the time they take the survey, their mentality while taking the survey, their gender, their feelings towards certain ideas, to name a few. The list goes on and on when it comes to surveying bias.
• A researcher is not necessary during data collection: The researcher doesn’t need to be present during data collection. It is practically impossible for the researcher to be present at every point of the data source, especially thinking about the various data sources.
• Useful for hypothesis: Use historical data to draw inferences of the current or future events. Conclusions can be drawn from the experience of past events and data available for them. 

Disadvantages of the method

Here are the disadvantages of the documentary research method:

• Limited data: Data is not always available, especially when you need to cross-verify a theory or strengthen your argument based on different forms of data.
• Inaccuracies: As the data is historical and published, there is almost no way of ascertaining if the data is accurate or not. 
• Incomplete documents: Often, documents can be incomplete, and there is no way of knowing if there are additional documents to refer to on the subject.
• Data out of context: The data that the researcher refers to may be out of context and may not be in line with the concept the researcher is trying to study. Its because the research goal is not thought of when creating the original data. Often, researchers have to make do with the available data at hand.

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Research Documentation

When publishing research , it is important to make documentation available so that readers can understand the details of the research design that the work reports. This includes all of the technical details and decisions that could influence how the findings are read or understood. Usually, this will involve producing a document along the lines of a methodological note or appendix. That document will describe how a given study was designed and how the design was carried out. The level of detail is in such a document should be relatively high. This page will describe some common approaches to compiling this kind of material and retaining the needed information in an organized fashion throughout the life of a research project.

• Research documentation provides the context to understanding the results of a given research output.
• There is no standard form for this documentation, and its location and format will depend on the type of research output produced.
• For academic materials, this documentation often takes the form of a structured methodological appendix.
• For policy outputs or online products, it may be appropriate to include an informative README webpage or document.
• The most important process for preparing this documentation will be retaining and organizing the needed information throughout the life of the project, so that the team will not have to search through communications or data archives for small details at publication time.

What to include in research documentation

Research documentation should include all the information that is needed to understand the underlying design for the research output. This can include descriptions of:

• Populations of interest that informed the study
• Methods of sampling or other sources of data about selecting the units of observation that were actually included in the study
• Power calculations and pre-analysis plans
• Field work, including data collection or experimental manipulation, such as study protocols and monitoring or quality assurance information
• Data collection tools such as survey instruments, search keywords, and instructions or code for API requests or database queries
• Statistical approaches such as definitions of key constructed indicators, corrections or adjustments to data, and precise definitions of estimators and estimation procedures
• Data completeness, including non-observed units or quantities that were planned or "tracking" information

All of the research documentation taken together should broadly allow a reader to understand how information was gathered, what it represents, what kind of information and data files to expect, and how to relate that information to the results of the research. Research documentation is not a complete guide to data, however; it does not need to provide the level of detail or instructions that would enable a reader to approach different research questions using the same data.

Documentation will take different forms depending on the information included. Much of it will be written narrative rather than, for example, formal datasets . Understanding research documentation should not require the user to have any special software or to undertake any analytical tasks themselves. Relevant datasets (such as tracking of units of observation over time) might be included alongside the documentation, but the documentation should summarize in narrative form all the information from that dataset that is likely to affect the interpretation of the research.

Structuring research documentation as a publication appendix

If you are preparing documentation to accompany the publication of an academic output such as a working paper or journal article, the most common form of research documentation is a structured supplemental appendix. Check the journal's publication process for details. Some publishers allow unlimited supplementary materials to be included in a format such as an author-created document. These materials may or may not be included under the peer review of the main manuscript and might only be intended to provide context for readers and reviewers. In this case you should provide complete information in that material. Other publishers expect all supplementary materials to be read and reviewed as part of the publication process. In this case you should provide the minimum additional detail required to understand the research here (since much of the appendix will likely be taken up by supplementary results rather than documentation), and consider other methods for releasing complete documentation, such as self-publication on OSF or Zenodo.

Since there is unlimited space and you may have a large amount of material to include in a documentation appendix, organization is essential. It is appropriate to have several appendices that cover different aspects of the research. For example, Appendix A may include information about the study population and data, such as the total number of units available for observation , the number selected or included for observation, the number successfully included, and descriptive statistics about subgroups, strata, clusters, or other units relevant to the research. It could be accompanied by a tracking dataset with full information about the process. Appendix B might include information about an intended experimental manipulation in one section, and information about implementation, take-up, and fidelity in a second section. It could be accompanied by a dataset with key indicators. Appendix C might include data collection protocols and definitions of constructed variables and comparisons with alternative definitions, and be accompanied by data collection instruments and illustrative figures. Each appendix should included relevant references. Supplementary exhibits should be numbered to correspond with the appendix they pertain to. More granular appendices are generally preferable so that referencing and numbering remains relatively uncomplicated.

There have been many attempts to standardized some of these elements, such as the STROBE and CONSORT reporting checklists . Journals will let you know if they expect these exact templates to be followed. Even if they are not required, such templates can still be used directly or to provide inspiration or structure for the materials you might want to include.

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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. 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 subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
• Next: Quantitative Research >>
• Last Updated: Sep 6, 2024 8:59 PM
• URL: https://guides.lib.berkeley.edu/researchmethods

Documentary Research Method: New Dimensions

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Document Research

Document research method refers to the analysis of documents that contains information about the scenario or event under consideration. It is used to investigate, categorize and analyze physical sources, most commonly written documents, in the social, public or digital world. This research method is just as good as and sometimes even more cost effective than the surveys, in-depth interviews or other observation based methods such as ethnography.

Quick details:

Preparation:

Documents to be researched

Deliverables:

Research notes, Documentation, Insights

More about Document Research

A document is defined as written text. Documents can be files, statistical data, records of official or unofficial nature providing an account of an event, images, other written material that can be accessed in a social, public or digital context. For example, institutional memoranda and reports, census publications, government pronouncements and proceedings, diaries and other written, visual and pictorial sources in different forms and so on are socially, publically or digitally accessible either openly or on request.

Document research is not a standalone method; it is usually used in conjunction with other design methods. Document research is employed when the researcher has questions to which they seek answers. It is not as helpful in an open inquiry to determine patterns as the number of documents that would need to be investigated can be huge, turning the researcher’s task into a never-ending exercise. Therefore, This research method is often used only as a supplement to the other research methods.

Along with surveys and ethnography, document research is one of the three major types of social research and arguably has been the most widely used of the three, to study needs, behavior and expectations of user groups. The analysis of the documents in document research is either quantitative or qualitative analysis (or both). The key issues surrounding types of documents and our ability to use them as reliable sources of evidence on the user groups must be considered by all who use documents in their research.

Advantages of Document Research

1. availability.

Document research method uses documents that are public or can be accessed on request if private.

2. Time & Cost effective

As the phenomenon being investigated is clearly defined before the method is exercised, the research is focused and closed. This saves a lot of time for the researcher and also costs that would have been incurred if an expert was consulted for the study.

3. Unbiased Collection Process

As the collection process doesn’t involve direct interaction of the researcher with the user groups or author of the documents, the chances of introducing bias stays low. Again, if the document is of the statistical record type, then the data being collected is based on facts that can be verified and cross-checked for errors.

4. Researcher Presence

The researcher is not required to be present at the time of data collection.

Disadvantages of Document Research

1. limited by available data.

As the data or documents that are available on the phenomenon being investigated as the primary resources for the study, the findings will be based on only the data that is documented on the subject.

2. Errors in written material

If there are errors in the documents being referred, these errors will render erroneous findings as well.

3. Out of context

If the documents studied are out of context, they will not contribute meaning to the study or will not lead to an insightful findings.

4. Preparation before analysis

The preparation required before document analysis is performed is a task in itself. The efforts are usually directed toward recruiting the researchers, identifying sources, shortlisting the material to be researched and analyzed, among others.

Think Design's recommendation

More often than not, any design project starts with some kind of Document Research or the other. It is predominantly a secondary research method; however, the researcher/ designer is using the documented material for his own understanding of the context. 

Do not use document research as a stand-alone method and do not proceed with your design assuming that the documents you studied have provided you with all the answers. This method compliments other methods and is usually a good starting point.

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Research is a study to find answers and solutions to scientific, social and literary problems through a systematic way. It is a cautious, orderly and patient investigation in any field of knowledge undertaken to form facts or principles. It is a well-thought-out inquiry that uses an acceptable specific methodology to gather, analyze and interpret information in order to resolve problems or answer questions and, in general, to create new knowledge. It can therefore simply be defined as a journey leading to the finding of new knowledge with the revision of evidence, theories and applications. Any research work undertaken must make an innovative contribution to the current information in the applicable discipline. In research, whatever the focus may be, the study must be an industrious and systematic investigation with proper methods for the discovery, analysis or updating of data for the application of research findings to refine knowledge in chosen subjects or disciplines. In research, the research methodology must be complemented by proper stylesheets for formatting in-text citations, works cited/end notes/footnotes and bibliography and a literature review must be carried out. In a serious academic research, methodology, style-sheets and review of literature have utmost importance.

Bibliometrics is the discipline where quantitative methods were employed to probe scientific communication process by measuring and analyzing various aspects of written documents. It helps to monitor growth of literature and patterns of research. This paper examines the articles published in Journal of Documentation for authorship pattern, degree of collaboration, geographical distribution of papers and citation analysis. The studies carried out for this paper found that majority of papers are multi- authored. The degree of collaboration is found to be 0.51. The geographical distribution reveals that the contribution by United Kingdom is the highest. The average citations per paper are 43.

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Evaluating nursing documentation - research designs and methods: systematic review

Affiliation.

• 1 Health and Human Services Informatics, Department of Health Policy and Management, University of Kuopio, Finland. [email protected]
• PMID: 19222644
• DOI: 10.1111/j.1365-2648.2008.04914.x

Aim: This paper is a report of a review conducted to assess the research methods applied in the evaluation of nursing documentation.

Data sources: The material was drawn from three databases: CINAHL, PubMed and Cochrane using the keywords nursing documentation, nursing care plan, nursing record system, evaluation and assessment. The search was confined to relevant electronically-retrievable studies published in the English language from 2000 to 2007. This yielded 41 studies, including two reviews.

Methods: Content analysis produced a classification into three themes: nursing documentation, patient-centred documentation and standardized documentation. Each study was assessed according to its research design, methodology, sample size and focus of data collection. In addition, the studies categorized under the heading of standardized documentation were assessed in terms of their outcomes.

Results: Most of the studies (n = 19) focused on patient-centred documentation. Most (n = 20) were retrospective studies and used data collected from patient records (n = 35). An audit instrument was used to assess nursing documentation in almost all the studies. Studies classified under the heading of standardized documentation showed more positive than negative effects with respect to quality, the nursing process and terminology use, knowledge level and acceptance of computer use in documentation.

Conclusion: The use of structured nursing terminology in electronic patient record systems will extend the scope of documentation research from assessing the quality of documentation to measuring patient outcomes. More data should also be collected from patients and family members when evaluating nursing documentation.

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Event-Driven Process Methodology Notation for Information Processing Research

• INFORMATION PROCESSES
• Published: 25 September 2024
• Volume 58 , pages 243–254, ( 2024 )

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• L. A. Mylnikov 1 , 2 ,
• A. D. Saltykova 1 &
• Z. Avramovic 3  

This paper addresses the problem of improving information infrastructure and decision support systems in dynamic external and internal organizational environments. It provides an overview of the new event-driven process methodology notation for information infrastructure and the assessing information processing effectiveness. The main types of information processes, their differences and research methods are presented. The procedural models given in this paper are intended for research and comparison of information processes according to specified performance criteria. Different information processes types and their formalization techniques are given.

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The study was supported by the Government of the Perm krai, project no. C-26/692.

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National Research University Higher School of Economics, Moscow, Russia

L. A. Mylnikov & A. D. Saltykova

Perm National Research Polytechnic University, Perm, Russia

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Mylnikov, L.A., Saltykova, A.D. & Avramovic, Z. Event-Driven Process Methodology Notation for Information Processing Research. Autom. Doc. Math. Linguist. 58 , 243–254 (2024). https://doi.org/10.3103/S0005105524700183

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Received : 25 April 2024

Published : 25 September 2024

Issue Date : August 2024

DOI : https://doi.org/10.3103/S0005105524700183

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