research method planning

How to write a research plan: Step-by-step guide

Last updated

30 January 2024

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Today’s businesses and institutions rely on data and analytics to inform their product and service decisions. These metrics influence how organizations stay competitive and inspire innovation. However, gathering data and insights requires carefully constructed research, and every research project needs a roadmap. This is where a research plan comes into play.

There’s general research planning; then there’s an official, well-executed research plan. Whatever data-driven research project you’re gearing up for, the research plan will be your framework for execution. The plan should also be detailed and thorough, with a diligent set of criteria to formulate your research efforts. Not including these key elements in your plan can be just as harmful as having no plan at all.

Read this step-by-step guide for writing a detailed research plan that can apply to any project, whether it’s scientific, educational, or business-related.

• What is a research plan?

A research plan is a documented overview of a project in its entirety, from end to end. It details the research efforts, participants, and methods needed, along with any anticipated results. It also outlines the project’s goals and mission, creating layers of steps to achieve those goals within a specified timeline.

Without a research plan, you and your team are flying blind, potentially wasting time and resources to pursue research without structured guidance.

The principal investigator, or PI, is responsible for facilitating the research oversight. They will create the research plan and inform team members and stakeholders of every detail relating to the project. The PI will also use the research plan to inform decision-making throughout the project.

• Why do you need a research plan?

Create a research plan before starting any official research to maximize every effort in pursuing and collecting the research data. Crucially, the plan will model the activities needed at each phase of the research project.

Like any roadmap, a research plan serves as a valuable tool providing direction for those involved in the project—both internally and externally. It will keep you and your immediate team organized and task-focused while also providing necessary definitions and timelines so you can execute your project initiatives with full understanding and transparency.

External stakeholders appreciate a working research plan because it’s a great communication tool, documenting progress and changing dynamics as they arise. Any participants of your planned research sessions will be informed about the purpose of your study, while the exercises will be based on the key messaging outlined in the official plan.

Here are some of the benefits of creating a research plan document for every project:

Project organization and structure

Well-informed participants

All stakeholders and teams align in support of the project

Clearly defined project definitions and purposes

Distractions are eliminated, prioritizing task focus

Timely management of individual task schedules and roles

Costly reworks are avoided

• What should a research plan include?

The different aspects of your research plan will depend on the nature of the project. However, most official research plan documents will include the core elements below. Each aims to define the problem statement, devising an official plan for seeking a solution.

Specific project goals and individual objectives

Ideal strategies or methods for reaching those goals

Required resources

Descriptions of the target audience, sample sizes, demographics, and scopes

Key performance indicators (KPIs)

Project background

Research and testing support

Preliminary studies and progress reporting mechanisms

Cost estimates and change order processes

Depending on the research project’s size and scope, your research plan could be brief—perhaps only a few pages of documented plans. Alternatively, it could be a fully comprehensive report. Either way, it’s an essential first step in dictating your project’s facilitation in the most efficient and effective way.

• How to write a research plan for your project

When you start writing your research plan, aim to be detailed about each step, requirement, and idea. The more time you spend curating your research plan, the more precise your research execution efforts will be.

Account for every potential scenario, and be sure to address each and every aspect of the research.

Consider following this flow to develop a great research plan for your project:

Define your project’s purpose

Start by defining your project’s purpose. Identify what your project aims to accomplish and what you are researching. Remember to use clear language.

Thinking about the project’s purpose will help you set realistic goals and inform how you divide tasks and assign responsibilities. These individual tasks will be your stepping stones to reach your overarching goal.

Additionally, you’ll want to identify the specific problem, the usability metrics needed, and the intended solutions.

Know the following three things about your project’s purpose before you outline anything else:

What you’re doing

Why you’re doing it

What you expect from it

Identify individual objectives

With your overarching project objectives in place, you can identify any individual goals or steps needed to reach those objectives. Break them down into phases or steps. You can work backward from the project goal and identify every process required to facilitate it.

Be mindful to identify each unique task so that you can assign responsibilities to various team members. At this point in your research plan development, you’ll also want to assign priority to those smaller, more manageable steps and phases that require more immediate or dedicated attention.

Select research methods

Research methods might include any of the following:

User interviews: this is a qualitative research method where researchers engage with participants in one-on-one or group conversations. The aim is to gather insights into their experiences, preferences, and opinions to uncover patterns, trends, and data.

Field studies: this approach allows for a contextual understanding of behaviors, interactions, and processes in real-world settings. It involves the researcher immersing themselves in the field, conducting observations, interviews, or experiments to gather in-depth insights.

Card sorting: participants categorize information by sorting content cards into groups based on their perceived similarities. You might use this process to gain insights into participants’ mental models and preferences when navigating or organizing information on websites, apps, or other systems.

Focus groups: use organized discussions among select groups of participants to provide relevant views and experiences about a particular topic.

Diary studies: ask participants to record their experiences, thoughts, and activities in a diary over a specified period. This method provides a deeper understanding of user experiences, uncovers patterns, and identifies areas for improvement.

Five-second testing: participants are shown a design, such as a web page or interface, for just five seconds. They then answer questions about their initial impressions and recall, allowing you to evaluate the design’s effectiveness.

Surveys: get feedback from participant groups with structured surveys. You can use online forms, telephone interviews, or paper questionnaires to reveal trends, patterns, and correlations.

Tree testing: tree testing involves researching web assets through the lens of findability and navigability. Participants are given a textual representation of the site’s hierarchy (the “tree”) and asked to locate specific information or complete tasks by selecting paths.

Usability testing: ask participants to interact with a product, website, or application to evaluate its ease of use. This method enables you to uncover areas for improvement in digital key feature functionality by observing participants using the product.

Live website testing: research and collect analytics that outlines the design, usability, and performance efficiencies of a website in real time.

There are no limits to the number of research methods you could use within your project. Just make sure your research methods help you determine the following:

What do you plan to do with the research findings?

What decisions will this research inform? How can your stakeholders leverage the research data and results?

Recruit participants and allocate tasks

Next, identify the participants needed to complete the research and the resources required to complete the tasks. Different people will be proficient at different tasks, and having a task allocation plan will allow everything to run smoothly.

Prepare a thorough project summary

Every well-designed research plan will feature a project summary. This official summary will guide your research alongside its communications or messaging. You’ll use the summary while recruiting participants and during stakeholder meetings. It can also be useful when conducting field studies.

Ensure this summary includes all the elements of your research project. Separate the steps into an easily explainable piece of text that includes the following:

An introduction: the message you’ll deliver to participants about the interview, pre-planned questioning, and testing tasks.

Interview questions: prepare questions you intend to ask participants as part of your research study, guiding the sessions from start to finish.

An exit message: draft messaging your teams will use to conclude testing or survey sessions. These should include the next steps and express gratitude for the participant’s time.

Create a realistic timeline

While your project might already have a deadline or a results timeline in place, you’ll need to consider the time needed to execute it effectively.

Realistically outline the time needed to properly execute each supporting phase of research and implementation. And, as you evaluate the necessary schedules, be sure to include additional time for achieving each milestone in case any changes or unexpected delays arise.

For this part of your research plan, you might find it helpful to create visuals to ensure your research team and stakeholders fully understand the information.

Determine how to present your results

A research plan must also describe how you intend to present your results. Depending on the nature of your project and its goals, you might dedicate one team member (the PI) or assume responsibility for communicating the findings yourself.

In this part of the research plan, you’ll articulate how you’ll share the results. Detail any materials you’ll use, such as:

Presentations and slides

A project report booklet

A project findings pamphlet

Documents with key takeaways and statistics

Graphic visuals to support your findings

• Format your research plan

As you create your research plan, you can enjoy a little creative freedom. A plan can assume many forms, so format it how you see fit. Determine the best layout based on your specific project, intended communications, and the preferences of your teams and stakeholders.

Find format inspiration among the following layouts:

Written outlines

Narrative storytelling

Visual mapping

Graphic timelines

Remember, the research plan format you choose will be subject to change and adaptation as your research and findings unfold. However, your final format should ideally outline questions, problems, opportunities, and expectations.

• Research plan example

Imagine you’ve been tasked with finding out how to get more customers to order takeout from an online food delivery platform. The goal is to improve satisfaction and retain existing customers. You set out to discover why more people aren’t ordering and what it is they do want to order or experience. 

You identify the need for a research project that helps you understand what drives customer loyalty. But before you jump in and start calling past customers, you need to develop a research plan—the roadmap that provides focus, clarity, and realistic details to the project.

Here’s an example outline of a research plan you might put together:

Project title

Project members involved in the research plan

Purpose of the project (provide a summary of the research plan’s intent)

Objective 1 (provide a short description for each objective)

Objective 2

Objective 3

Proposed timeline

Audience (detail the group you want to research, such as customers or non-customers)

Budget (how much you think it might cost to do the research)

Risk factors/contingencies (any potential risk factors that may impact the project’s success)

Remember, your research plan doesn’t have to reinvent the wheel—it just needs to fit your project’s unique needs and aims.

Customizing a research plan template

Some companies offer research plan templates to help get you started. However, it may make more sense to develop your own customized plan template. Be sure to include the core elements of a great research plan with your template layout, including the following:

Introductions to participants and stakeholders

Background problems and needs statement

Significance, ethics, and purpose

Research methods, questions, and designs

Preliminary beliefs and expectations

Implications and intended outcomes

Realistic timelines for each phase

Conclusion and presentations

How many pages should a research plan be?

Generally, a research plan can vary in length between 500 to 1,500 words. This is roughly three pages of content. More substantial projects will be 2,000 to 3,500 words, taking up four to seven pages of planning documents.

What is the difference between a research plan and a research proposal?

A research plan is a roadmap to success for research teams. A research proposal, on the other hand, is a dissertation aimed at convincing or earning the support of others. Both are relevant in creating a guide to follow to complete a project goal.

What are the seven steps to developing a research plan?

While each research project is different, it’s best to follow these seven general steps to create your research plan:

Defining the problem

Identifying goals

Choosing research methods

Recruiting participants

Preparing the brief or summary

Establishing task timelines

Defining how you will present the findings

Should you be using a customer insights hub?

Do you want to discover previous research faster?

Do you share your research findings with others?

Do you analyze research data?

Start for free today, add your research, and get to key insights faster

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Rhode island school of design, create a research plan: research plan.

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A research plan is a framework that shows how you intend to approach your topic. The plan can take many forms: a written outline, a narrative, a visual/concept map or timeline. It's a document that will change and develop as you conduct your research. Components of a research plan

1. Research conceptualization - introduces your research question

2. Research methodology - describes your approach to the research question

3. Literature review, critical evaluation and synthesis - systematic approach to locating,

    reviewing and evaluating the work (text, exhibitions, critiques, etc) relating to your topic

4. Communication - geared toward an intended audience, shows evidence of your inquiry

Research conceptualization refers to the ability to identify specific research questions, problems or opportunities that are worthy of inquiry. Research conceptualization also includes the skills and discipline that go beyond the initial moment of conception, and which enable the researcher to formulate and develop an idea into something researchable ( Newbury 373).

Research methodology refers to the knowledge and skills required to select and apply appropriate methods to carry through the research project ( Newbury 374) .

Method describes a single mode of proceeding; methodology describes the overall process.

Method - a way of doing anything especially according to a defined and regular plan; a mode of procedure in any activity

Methodology - the study of the direction and implications of empirical research, or the sustainability of techniques employed in it; a method or body of methods used in a particular field of study or activity *Browse a list of research methodology books  or this guide on Art & Design Research

Literature Review, critical evaluation & synthesis

A literature review is a systematic approach to locating, reviewing, and evaluating the published work and work in progress of scholars, researchers, and practitioners on a given topic.

Critical evaluation and synthesis is the ability to handle (or process) existing sources. It includes knowledge of the sources of literature and contextual research field within which the person is working ( Newbury 373).

Literature reviews are done for many reasons and situations. Here's a short list:

Sources to consult while conducting a literature review:

Online catalogs of local, regional, national, and special libraries

meta-catalogs such as worldcat , Art Discovery Group , europeana , world digital library or RIBA

subject-specific online article databases (such as the Avery Index, JSTOR, Project Muse)

digital institutional repositories such as Digital Commons @RISD ; see Registry of Open Access Repositories

Open Access Resources recommended by RISD Research LIbrarians

works cited in scholarly books and articles

print bibliographies

the internet-locate major nonprofit, research institutes, museum, university, and government websites

search google scholar to locate grey literature & referenced citations

trade and scholarly publishers

fellow scholars and peers

Communication                              

Communication refers to the ability to

• structure a coherent line of inquiry
• communicate your findings to your intended audience
• make skilled use of visual material to express ideas for presentations, writing, and the creation of exhibitions ( Newbury 374)

Research plan framework: Newbury, Darren. "Research Training in the Creative Arts and Design." The Routledge Companion to Research in the Arts . Ed. Michael Biggs and Henrik Karlsson. New York: Routledge, 2010. 368-87. Print.

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Except where otherwise noted, this guide is subject to a Creative Commons Attribution license

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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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The Ultimate Guide To Research Methodology

Research methodology is a crucial aspect of any investigative process, serving as the blueprint for the entire research journey. If you are stuck in the methodology section of your research paper , then this blog will guide you on what is a research methodology, its types and how to successfully conduct one. 

Table of Contents

What Is Research Methodology?

Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings. 

Research methodology is not confined to a singular approach; rather, it encapsulates a diverse range of methods tailored to the specific requirements of the research objectives.

Here is why Research methodology is important in academic and professional settings.

Facilitating Rigorous Inquiry

Research methodology forms the backbone of rigorous inquiry. It provides a structured approach that aids researchers in formulating precise thesis statements , selecting appropriate methodologies, and executing systematic investigations. This, in turn, enhances the quality and credibility of the research outcomes.

Ensuring Reproducibility And Reliability

In both academic and professional contexts, the ability to reproduce research outcomes is paramount. A well-defined research methodology establishes clear procedures, making it possible for others to replicate the study. This not only validates the findings but also contributes to the cumulative nature of knowledge.

Guiding Decision-Making Processes

In professional settings, decisions often hinge on reliable data and insights. Research methodology equips professionals with the tools to gather pertinent information, analyze it rigorously, and derive meaningful conclusions.

This informed decision-making is instrumental in achieving organizational goals and staying ahead in competitive environments.

Contributing To Academic Excellence

For academic researchers, adherence to robust research methodology is a hallmark of excellence. Institutions value research that adheres to high standards of methodology, fostering a culture of academic rigour and intellectual integrity. Furthermore, it prepares students with critical skills applicable beyond academia.

Enhancing Problem-Solving Abilities

Research methodology instills a problem-solving mindset by encouraging researchers to approach challenges systematically. It equips individuals with the skills to dissect complex issues, formulate hypotheses , and devise effective strategies for investigation.

Understanding Research Methodology

In the pursuit of knowledge and discovery, understanding the fundamentals of research methodology is paramount. 

Basics Of Research

Research, in its essence, is a systematic and organized process of inquiry aimed at expanding our understanding of a particular subject or phenomenon. It involves the exploration of existing knowledge, the formulation of hypotheses, and the collection and analysis of data to draw meaningful conclusions. 

Research is a dynamic and iterative process that contributes to the continuous evolution of knowledge in various disciplines.

Types of Research

Research takes on various forms, each tailored to the nature of the inquiry. Broadly classified, research can be categorized into two main types:

• Quantitative Research: This type involves the collection and analysis of numerical data to identify patterns, relationships, and statistical significance. It is particularly useful for testing hypotheses and making predictions.
• Qualitative Research: Qualitative research focuses on understanding the depth and details of a phenomenon through non-numerical data. It often involves methods such as interviews, focus groups, and content analysis, providing rich insights into complex issues.

Components Of Research Methodology

To conduct effective research, one must go through the different components of research methodology. These components form the scaffolding that supports the entire research process, ensuring its coherence and validity.

Research Design

Research design serves as the blueprint for the entire research project. It outlines the overall structure and strategy for conducting the study. The three primary types of research design are:

• Exploratory Research: Aimed at gaining insights and familiarity with the topic, often used in the early stages of research.
• Descriptive Research: Involves portraying an accurate profile of a situation or phenomenon, answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.
• Explanatory Research: Seeks to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how.’

Data Collection Methods

Choosing the right data collection methods is crucial for obtaining reliable and relevant information. Common methods include:

• Surveys and Questionnaires: Employed to gather information from a large number of respondents through standardized questions.
• Interviews: In-depth conversations with participants, offering qualitative insights.
• Observation: Systematic watching and recording of behaviour, events, or processes in their natural setting.

Data Analysis Techniques

Once data is collected, analysis becomes imperative to derive meaningful conclusions. Different methodologies exist for quantitative and qualitative data:

• Quantitative Data Analysis: Involves statistical techniques such as descriptive statistics, inferential statistics, and regression analysis to interpret numerical data.
• Qualitative Data Analysis: Methods like content analysis, thematic analysis, and grounded theory are employed to extract patterns, themes, and meanings from non-numerical data.

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Choosing a Research Method

Selecting an appropriate research method is a critical decision in the research process. It determines the approach, tools, and techniques that will be used to answer the research questions. 

Quantitative Research Methods

Quantitative research involves the collection and analysis of numerical data, providing a structured and objective approach to understanding and explaining phenomena.

Experimental Research

Experimental research involves manipulating variables to observe the effect on another variable under controlled conditions. It aims to establish cause-and-effect relationships.

Key Characteristics:

• Controlled Environment: Experiments are conducted in a controlled setting to minimize external influences.
• Random Assignment: Participants are randomly assigned to different experimental conditions.
• Quantitative Data: Data collected is numerical, allowing for statistical analysis.

Applications: Commonly used in scientific studies and psychology to test hypotheses and identify causal relationships.

Survey Research

Survey research gathers information from a sample of individuals through standardized questionnaires or interviews. It aims to collect data on opinions, attitudes, and behaviours.

• Structured Instruments: Surveys use structured instruments, such as questionnaires, to collect data.
• Large Sample Size: Surveys often target a large and diverse group of participants.
• Quantitative Data Analysis: Responses are quantified for statistical analysis.

Applications: Widely employed in social sciences, marketing, and public opinion research to understand trends and preferences.

Descriptive Research

Descriptive research seeks to portray an accurate profile of a situation or phenomenon. It focuses on answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.

• Observation and Data Collection: This involves observing and documenting without manipulating variables.
• Objective Description: Aim to provide an unbiased and factual account of the subject.
• Quantitative or Qualitative Data: T his can include both types of data, depending on the research focus.

Applications: Useful in situations where researchers want to understand and describe a phenomenon without altering it, common in social sciences and education.

Qualitative Research Methods

Qualitative research emphasizes exploring and understanding the depth and complexity of phenomena through non-numerical data.

A case study is an in-depth exploration of a particular person, group, event, or situation. It involves detailed, context-rich analysis.

• Rich Data Collection: Uses various data sources, such as interviews, observations, and documents.
• Contextual Understanding: Aims to understand the context and unique characteristics of the case.
• Holistic Approach: Examines the case in its entirety.

Applications: Common in social sciences, psychology, and business to investigate complex and specific instances.

Ethnography

Ethnography involves immersing the researcher in the culture or community being studied to gain a deep understanding of their behaviours, beliefs, and practices.

• Participant Observation: Researchers actively participate in the community or setting.
• Holistic Perspective: Focuses on the interconnectedness of cultural elements.
• Qualitative Data: In-depth narratives and descriptions are central to ethnographic studies.

Applications: Widely used in anthropology, sociology, and cultural studies to explore and document cultural practices.

Grounded Theory

Grounded theory aims to develop theories grounded in the data itself. It involves systematic data collection and analysis to construct theories from the ground up.

• Constant Comparison: Data is continually compared and analyzed during the research process.
• Inductive Reasoning: Theories emerge from the data rather than being imposed on it.
• Iterative Process: The research design evolves as the study progresses.

Applications: Commonly applied in sociology, nursing, and management studies to generate theories from empirical data.

Research design is the structural framework that outlines the systematic process and plan for conducting a study. It serves as the blueprint, guiding researchers on how to collect, analyze, and interpret data.

Exploratory, Descriptive, And Explanatory Designs

Exploratory design.

Exploratory research design is employed when a researcher aims to explore a relatively unknown subject or gain insights into a complex phenomenon.

• Flexibility: Allows for flexibility in data collection and analysis.
• Open-Ended Questions: Uses open-ended questions to gather a broad range of information.
• Preliminary Nature: Often used in the initial stages of research to formulate hypotheses.

Applications: Valuable in the early stages of investigation, especially when the researcher seeks a deeper understanding of a subject before formalizing research questions.

Descriptive Design

Descriptive research design focuses on portraying an accurate profile of a situation, group, or phenomenon.

• Structured Data Collection: Involves systematic and structured data collection methods.
• Objective Presentation: Aims to provide an unbiased and factual account of the subject.
• Quantitative or Qualitative Data: Can incorporate both types of data, depending on the research objectives.

Applications: Widely used in social sciences, marketing, and educational research to provide detailed and objective descriptions.

Explanatory Design

Explanatory research design aims to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how’ behind observed relationships.

• Causal Relationships: Seeks to establish causal relationships between variables.
• Controlled Variables : Often involves controlling certain variables to isolate causal factors.
• Quantitative Analysis: Primarily relies on quantitative data analysis techniques.

Applications: Commonly employed in scientific studies and social sciences to delve into the underlying reasons behind observed patterns.

Cross-Sectional Vs. Longitudinal Designs

Cross-sectional design.

Cross-sectional designs collect data from participants at a single point in time.

• Snapshot View: Provides a snapshot of a population at a specific moment.
• Efficiency: More efficient in terms of time and resources.
• Limited Temporal Insights: Offers limited insights into changes over time.

Applications: Suitable for studying characteristics or behaviours that are stable or not expected to change rapidly.

Longitudinal Design

Longitudinal designs involve the collection of data from the same participants over an extended period.

• Temporal Sequence: Allows for the examination of changes over time.
• Causality Assessment: Facilitates the assessment of cause-and-effect relationships.
• Resource-Intensive: Requires more time and resources compared to cross-sectional designs.

Applications: Ideal for studying developmental processes, trends, or the impact of interventions over time.

Experimental Vs Non-experimental Designs

Experimental design.

Experimental designs involve manipulating variables under controlled conditions to observe the effect on another variable.

• Causality Inference: Enables the inference of cause-and-effect relationships.
• Quantitative Data: Primarily involves the collection and analysis of numerical data.

Applications: Commonly used in scientific studies, psychology, and medical research to establish causal relationships.

Non-Experimental Design

Non-experimental designs observe and describe phenomena without manipulating variables.

• Natural Settings: Data is often collected in natural settings without intervention.
• Descriptive or Correlational: Focuses on describing relationships or correlations between variables.
• Quantitative or Qualitative Data: This can involve either type of data, depending on the research approach.

Applications: Suitable for studying complex phenomena in real-world settings where manipulation may not be ethical or feasible.

Effective data collection is fundamental to the success of any research endeavour. 

Designing Effective Surveys

Objective Design:

• Clearly define the research objectives to guide the survey design.
• Craft questions that align with the study’s goals and avoid ambiguity.

Structured Format:

• Use a structured format with standardized questions for consistency.
• Include a mix of closed-ended and open-ended questions for detailed insights.

Pilot Testing:

• Conduct pilot tests to identify and rectify potential issues with survey design.
• Ensure clarity, relevance, and appropriateness of questions.

Sampling Strategy:

• Develop a robust sampling strategy to ensure a representative participant group.
• Consider random sampling or stratified sampling based on the research goals.

Conducting Interviews

Establishing Rapport:

• Build rapport with participants to create a comfortable and open environment.
• Clearly communicate the purpose of the interview and the value of participants’ input.

Open-Ended Questions:

• Frame open-ended questions to encourage detailed responses.
• Allow participants to express their thoughts and perspectives freely.

Active Listening:

• Practice active listening to understand areas and gather rich data.
• Avoid interrupting and maintain a non-judgmental stance during the interview.

Ethical Considerations:

• Obtain informed consent and assure participants of confidentiality.
• Be transparent about the study’s purpose and potential implications.

Observation

1. participant observation.

Immersive Participation:

• Actively immerse yourself in the setting or group being observed.
• Develop a deep understanding of behaviours, interactions, and context.

Field Notes:

• Maintain detailed and reflective field notes during observations.
• Document observed patterns, unexpected events, and participant reactions.

Ethical Awareness:

• Be conscious of ethical considerations, ensuring respect for participants.
• Balance the role of observer and participant to minimize bias.

2. Non-participant Observation

Objective Observation:

• Maintain a more detached and objective stance during non-participant observation.
• Focus on recording behaviours, events, and patterns without direct involvement.

Data Reliability:

• Enhance the reliability of data by reducing observer bias.
• Develop clear observation protocols and guidelines.

Contextual Understanding:

• Strive for a thorough understanding of the observed context.
• Consider combining non-participant observation with other methods for triangulation.

Archival Research

1. using existing data.

Identifying Relevant Archives:

• Locate and access archives relevant to the research topic.
• Collaborate with institutions or repositories holding valuable data.

Data Verification:

• Verify the accuracy and reliability of archived data.
• Cross-reference with other sources to ensure data integrity.

Ethical Use:

• Adhere to ethical guidelines when using existing data.
• Respect copyright and intellectual property rights.

2. Challenges and Considerations

Incomplete or Inaccurate Archives:

• Address the possibility of incomplete or inaccurate archival records.
• Acknowledge limitations and uncertainties in the data.

Temporal Bias:

• Recognize potential temporal biases in archived data.
• Consider the historical context and changes that may impact interpretation.

Access Limitations:

• Address potential limitations in accessing certain archives.
• Seek alternative sources or collaborate with institutions to overcome barriers.

Common Challenges in Research Methodology

Conducting research is a complex and dynamic process, often accompanied by a myriad of challenges. Addressing these challenges is crucial to ensure the reliability and validity of research findings.

Sampling Issues

Sampling bias:.

• The presence of sampling bias can lead to an unrepresentative sample, affecting the generalizability of findings.
• Employ random sampling methods and ensure the inclusion of diverse participants to reduce bias.

Sample Size Determination:

• Determining an appropriate sample size is a delicate balance. Too small a sample may lack statistical power, while an excessively large sample may strain resources.
• Conduct a power analysis to determine the optimal sample size based on the research objectives and expected effect size.

Data Quality And Validity

Measurement error:.

• Inaccuracies in measurement tools or data collection methods can introduce measurement errors, impacting the validity of results.
• Pilot test instruments, calibrate equipment, and use standardized measures to enhance the reliability of data.

Construct Validity:

• Ensuring that the chosen measures accurately capture the intended constructs is a persistent challenge.
• Use established measurement instruments and employ multiple measures to assess the same construct for triangulation.

Time And Resource Constraints

Timeline pressures:.

• Limited timeframes can compromise the depth and thoroughness of the research process.
• Develop a realistic timeline, prioritize tasks, and communicate expectations with stakeholders to manage time constraints effectively.

Resource Availability:

• Inadequate resources, whether financial or human, can impede the execution of research activities.
• Seek external funding, collaborate with other researchers, and explore alternative methods that require fewer resources.

Managing Bias in Research

Selection bias:.

• Selecting participants in a way that systematically skews the sample can introduce selection bias.
• Employ randomization techniques, use stratified sampling, and transparently report participant recruitment methods.

Confirmation Bias:

• Researchers may unintentionally favour information that confirms their preconceived beliefs or hypotheses.
• Adopt a systematic and open-minded approach, use blinded study designs, and engage in peer review to mitigate confirmation bias.

Tips On How To Write A Research Methodology

Conducting successful research relies not only on the application of sound methodologies but also on strategic planning and effective collaboration. Here are some tips to enhance the success of your research methodology:

Tip 1. Clear Research Objectives

Well-defined research objectives guide the entire research process. Clearly articulate the purpose of your study, outlining specific research questions or hypotheses.

Tip 2. Comprehensive Literature Review

A thorough literature review provides a foundation for understanding existing knowledge and identifying gaps. Invest time in reviewing relevant literature to inform your research design and methodology.

Tip 3. Detailed Research Plan

A detailed plan serves as a roadmap, ensuring all aspects of the research are systematically addressed. Develop a detailed research plan outlining timelines, milestones, and tasks.

Tip 4. Ethical Considerations

Ethical practices are fundamental to maintaining the integrity of research. Address ethical considerations early, obtain necessary approvals, and ensure participant rights are safeguarded.

Tip 5. Stay Updated On Methodologies

Research methodologies evolve, and staying updated is essential for employing the most effective techniques. Engage in continuous learning by attending workshops, conferences, and reading recent publications.

Tip 6. Adaptability In Methods

Unforeseen challenges may arise during research, necessitating adaptability in methods. Be flexible and willing to modify your approach when needed, ensuring the integrity of the study.

Tip 7. Iterative Approach

Research is often an iterative process, and refining methods based on ongoing findings enhance the study’s robustness. Regularly review and refine your research design and methods as the study progresses.

Frequently Asked Questions

What is the research methodology.

Research methodology is the systematic process of planning, executing, and evaluating scientific investigation. It encompasses the techniques, tools, and procedures used to collect, analyze, and interpret data, ensuring the reliability and validity of research findings.

What are the methodologies in research?

Research methodologies include qualitative and quantitative approaches. Qualitative methods involve in-depth exploration of non-numerical data, while quantitative methods use statistical analysis to examine numerical data. Mixed methods combine both approaches for a comprehensive understanding of research questions.

How to write research methodology?

To write a research methodology, clearly outline the study’s design, data collection, and analysis procedures. Specify research tools, participants, and sampling methods. Justify choices and discuss limitations. Ensure clarity, coherence, and alignment with research objectives for a robust methodology section.

How to write the methodology section of a research paper?

In the methodology section of a research paper, describe the study’s design, data collection, and analysis methods. Detail procedures, tools, participants, and sampling. Justify choices, address ethical considerations, and explain how the methodology aligns with research objectives, ensuring clarity and rigour.

What is mixed research methodology?

Mixed research methodology combines both qualitative and quantitative research approaches within a single study. This approach aims to enhance the details and depth of research findings by providing a more comprehensive understanding of the research problem or question.

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How to plan a research project

Whether for a paper or a thesis, define your question, review the work of others – and leave yourself open to discovery.

by Brooke Harrington   + BIO

is professor of sociology at Dartmouth College in New Hampshire. Her research has won international awards both for scholarly quality and impact on public life. She has published dozens of articles and three books, most recently the bestseller Capital without Borders (2016), now translated into five languages.

Edited by Sam Haselby

Need to know

‘When curiosity turns to serious matters, it’s called research.’ – From Aphorisms (1880-1905) by Marie von Ebner-Eschenbach

Planning research projects is a time-honoured intellectual exercise: one that requires both creativity and sharp analytical skills. The purpose of this Guide is to make the process systematic and easy to understand. While there is a great deal of freedom and discovery involved – from the topics you choose, to the data and methods you apply – there are also some norms and constraints that obtain, no matter what your academic level or field of study. For those in high school through to doctoral students, and from art history to archaeology, research planning involves broadly similar steps, including: formulating a question, developing an argument or predictions based on previous research, then selecting the information needed to answer your question.

Some of this might sound self-evident but, as you’ll find, research requires a different way of approaching and using information than most of us are accustomed to in everyday life. That is why I include orienting yourself to knowledge-creation as an initial step in the process. This is a crucial and underappreciated phase in education, akin to making the transition from salaried employment to entrepreneurship: suddenly, you’re on your own, and that requires a new way of thinking about your work.

What follows is a distillation of what I’ve learned about this process over 27 years as a professional social scientist. It reflects the skills that my own professors imparted in the sociology doctoral programme at Harvard, as well as what I learned later on as a research supervisor for Ivy League PhD and MA students, and then as the author of award-winning scholarly books and articles. It can be adapted to the demands of both short projects (such as course term papers) and long ones, such as a thesis.

At its simplest, research planning involves the four distinct steps outlined below: orienting yourself to knowledge-creation; defining your research question; reviewing previous research on your question; and then choosing relevant data to formulate your own answers. Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won’t delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis. Instead, the fourth part of this section will outline some basic strategies you could use in planning a data-selection and analysis process appropriate to your research question.

Step 1: Orient yourself

Planning and conducting research requires you to make a transition, from thinking like a consumer of information to thinking like a producer of information. That sounds simple, but it’s actually a complex task. As a practical matter, this means putting aside the mindset of a student, which treats knowledge as something created by other people. As students, we are often passive receivers of knowledge: asked to do a specified set of readings, then graded on how well we reproduce what we’ve read.

Researchers, however, must take on an active role as knowledge producers . Doing research requires more of you than reading and absorbing what other people have written: you have to engage in a dialogue with it. That includes arguing with previous knowledge and perhaps trying to show that ideas we have accepted as given are actually wrong or incomplete. For example, rather than simply taking in the claims of an author you read, you’ll need to draw out the implications of those claims: if what the author is saying is true, what else does that suggest must be true? What predictions could you make based on the author’s claims?

In other words, rather than treating a reading as a source of truth – even if it comes from a revered source, such as Plato or Marie Curie – this orientation step asks you to treat the claims you read as provisional and subject to interrogation. That is one of the great pieces of wisdom that science and philosophy can teach us: that the biggest advances in human understanding have been made not by being correct about trivial things, but by being wrong in an interesting way . For example, Albert Einstein was wrong about quantum mechanics, but his arguments about it with his fellow physicist Niels Bohr have led to some of the biggest breakthroughs in science, even a century later.

Step 2: Define your research question

Students often give this step cursory attention, but experienced researchers know that formulating a good question is sometimes the most difficult part of the research planning process. That is because the precise language of the question frames the rest of the project. It’s therefore important to pose the question carefully, in a way that’s both possible to answer and likely to yield interesting results. Of course, you must choose a question that interests you, but that’s only the beginning of what’s likely to be an iterative process: most researchers come back to this step repeatedly, modifying their questions in light of previous research, resource limitations and other considerations.

Researchers face limits in terms of time and money. They, like everyone else, have to pose research questions that they can plausibly answer given the constraints they face. For example, it would be inadvisable to frame a project around the question ‘What are the roots of the Arab-Israeli conflict?’ if you have only a week to develop an answer and no background on that topic. That’s not to limit your imagination: you can come up with any question you’d like. But it typically does require some creativity to frame a question that you can answer well – that is, by investigating thoroughly and providing new insights – within the limits you face.

In addition to being interesting to you, and feasible within your resource constraints, the third and most important characteristic of a ‘good’ research topic is whether it allows you to create new knowledge. It might turn out that your question has already been asked and answered to your satisfaction: if so, you’ll find out in the next step of this process. On the other hand, you might come up with a research question that hasn’t been addressed previously. Before you get too excited about breaking uncharted ground, consider this: a lot of potentially researchable questions haven’t been studied for good reason ; they might have answers that are trivial or of very limited interest. This could include questions such as ‘Why does the area of a circle equal π r²?’ or ‘Did winter conditions affect Napoleon’s plans to invade Russia?’ Of course, you might be able to make the argument that a seemingly trivial question is actually vitally important, but you must be prepared to back that up with convincing evidence. The exercise in the ‘Learn More’ section below will help you think through some of these issues.

Finally, scholarly research questions must in some way lead to new and distinctive insights. For example, lots of people have studied gender roles in sports teams; what can you ask that hasn’t been asked before? Reinventing the wheel is the number-one no-no in this endeavour. That’s why the next step is so important: reviewing previous research on your topic. Depending on what you find in that step, you might need to revise your research question; iterating between your question and the existing literature is a normal process. But don’t worry: it doesn’t go on forever. In fact, the iterations taper off – and your research question stabilises – as you develop a firm grasp of the current state of knowledge on your topic.

Step 3: Review previous research

In academic research, from articles to books, it’s common to find a section called a ‘literature review’. The purpose of that section is to describe the state of the art in knowledge on the research question that a project has posed. It demonstrates that researchers have thoroughly and systematically reviewed the relevant findings of previous studies on their topic, and that they have something novel to contribute.

Your own research project should include something like this, even if it’s a high-school term paper. In the research planning process, you’ll want to list at least half a dozen bullet points stating the major findings on your topic by other people. In relation to those findings, you should be able to specify where your project could provide new and necessary insights. There are two basic rhetorical positions one can take in framing the novelty-plus-importance argument required of academic research:

• Position 1 requires you to build on or extend a set of existing ideas; that means saying something like: ‘Person A has argued that X is true about gender; this implies Y, which has not yet been tested. My project will test Y, and if I find evidence to support it, that will change the way we understand gender.’
• Position 2 is to argue that there is a gap in existing knowledge, either because previous research has reached conflicting conclusions or has failed to consider something important. For example, one could say that research on middle schoolers and gender has been limited by being conducted primarily in coeducational environments, and that findings might differ dramatically if research were conducted in more schools where the student body was all-male or all-female.

Your overall goal in this step of the process is to show that your research will be part of a larger conversation: that is, how your project flows from what’s already known, and how it advances, extends or challenges that existing body of knowledge. That will be the contribution of your project, and it constitutes the motivation for your research.

Two things are worth mentioning about your search for sources of relevant previous research. First, you needn’t look only at studies on your precise topic. For example, if you want to study gender-identity formation in schools, you shouldn’t restrict yourself to studies of schools; the empirical setting (schools) is secondary to the larger social process that interests you (how people form gender identity). That process occurs in many different settings, so cast a wide net. Second, be sure to use legitimate sources – meaning publications that have been through some sort of vetting process, whether that involves peer review (as with academic journal articles you might find via Google Scholar) or editorial review (as you’d find in well-known mass media publications, such as The Economist or The Washington Post ). What you’ll want to avoid is using unvetted sources such as personal blogs or Wikipedia. Why? Because anybody can write anything in those forums, and there is no way to know – unless you’re already an expert – if the claims you find there are accurate. Often, they’re not.

Step 4: Choose your data and methods

Whatever your research question is, eventually you’ll need to consider which data source and analytical strategy are most likely to provide the answers you’re seeking. One starting point is to consider whether your question would be best addressed by qualitative data (such as interviews, observations or historical records), quantitative data (such as surveys or census records) or some combination of both. Your ideas about data sources will, in turn, suggest options for analytical methods.

You might need to collect your own data, or you might find everything you need readily available in an existing dataset someone else has created. A great place to start is with a research librarian: university libraries always have them and, at public universities, those librarians can work with the public, including people who aren’t affiliated with the university. If you don’t happen to have a public university and its library close at hand, an ordinary public library can still be a good place to start: the librarians are often well versed in accessing data sources that might be relevant to your study, such as the census, or historical archives, or the Survey of Consumer Finances.

Because your task at this point is to plan research, rather than conduct it, the purpose of this step is not to commit you irrevocably to a course of action. Instead, your goal here is to think through a feasible approach to answering your research question. You’ll need to find out, for example, whether the data you want exist; if not, do you have a realistic chance of gathering the data yourself, or would it be better to modify your research question? In terms of analysis, would your strategy require you to apply statistical methods? If so, do you have those skills? If not, do you have time to learn them, or money to hire a research assistant to run the analysis for you?

Please be aware that qualitative methods in particular are not the casual undertaking they might appear to be. Many people make the mistake of thinking that only quantitative data and methods are scientific and systematic, while qualitative methods are just a fancy way of saying: ‘I talked to some people, read some old newspapers, and drew my own conclusions.’ Nothing could be further from the truth. In the final section of this guide, you’ll find some links to resources that will provide more insight on standards and procedures governing qualitative research, but suffice it to say: there are rules about what constitutes legitimate evidence and valid analytical procedure for qualitative data, just as there are for quantitative data.

Circle back and consider revising your initial plans

As you work through these four steps in planning your project, it’s perfectly normal to circle back and revise. Research planning is rarely a linear process. It’s also common for new and unexpected avenues to suggest themselves. As the sociologist Thorstein Veblen wrote in 1908 : ‘The outcome of any serious research can only be to make two questions grow where only one grew before.’ That’s as true of research planning as it is of a completed project. Try to enjoy the horizons that open up for you in this process, rather than becoming overwhelmed; the four steps, along with the two exercises that follow, will help you focus your plan and make it manageable.

Key points – How to plan a research project

• Planning a research project is essential no matter your academic level or field of study. There is no one ‘best’ way to design research, but there are certain guidelines that can be helpfully applied across disciplines.
• Orient yourself to knowledge-creation. Make the shift from being a consumer of information to being a producer of information.
• Define your research question. Your question frames the rest of your project, sets the scope, and determines the kinds of answers you can find.
• Review previous research on your question. Survey the existing body of relevant knowledge to ensure that your research will be part of a larger conversation.
• Choose your data and methods. For instance, will you be collecting qualitative data, via interviews, or numerical data, via surveys?
• Circle back and consider revising your initial plans. Expect your research question in particular to undergo multiple rounds of refinement as you learn more about your topic.

Good research questions tend to beget more questions. This can be frustrating for those who want to get down to business right away. Try to make room for the unexpected: this is usually how knowledge advances. Many of the most significant discoveries in human history have been made by people who were looking for something else entirely. There are ways to structure your research planning process without over-constraining yourself; the two exercises below are a start, and you can find further methods in the Links and Books section.

The following exercise provides a structured process for advancing your research project planning. After completing it, you’ll be able to do the following:

• describe clearly and concisely the question you’ve chosen to study
• summarise the state of the art in knowledge about the question, and where your project could contribute new insight
• identify the best strategy for gathering and analysing relevant data

In other words, the following provides a systematic means to establish the building blocks of your research project.

Exercise 1: Definition of research question and sources

This exercise prompts you to select and clarify your general interest area, develop a research question, and investigate sources of information. The annotated bibliography will also help you refine your research question so that you can begin the second assignment, a description of the phenomenon you wish to study.

Jot down a few bullet points in response to these two questions, with the understanding that you’ll probably go back and modify your answers as you begin reading other studies relevant to your topic:

• What will be the general topic of your paper?
• What will be the specific topic of your paper?

b) Research question(s)

Use the following guidelines to frame a research question – or questions – that will drive your analysis. As with Part 1 above, you’ll probably find it necessary to change or refine your research question(s) as you complete future assignments.

• Your question should be phrased so that it can’t be answered with a simple ‘yes’ or ‘no’.
• Your question should have more than one plausible answer.
• Your question should draw relationships between two or more concepts; framing the question in terms of How? or What? often works better than asking Why ?

c) Annotated bibliography

Most or all of your background information should come from two sources: scholarly books and journals, or reputable mass media sources. You might be able to access journal articles electronically through your library, using search engines such as JSTOR and Google Scholar. This can save you a great deal of time compared with going to the library in person to search periodicals. General news sources, such as those accessible through LexisNexis, are acceptable, but should be cited sparingly, since they don’t carry the same level of credibility as scholarly sources. As discussed above, unvetted sources such as blogs and Wikipedia should be avoided, because the quality of the information they provide is unreliable and often misleading.

To create an annotated bibliography, provide the following information for at least 10 sources relevant to your specific topic, using the format suggested below.

Name of author(s):

Publication date:

Title of book, chapter, or article:

If a chapter or article, title of journal or book where they appear:

Brief description of this work, including main findings and methods ( c 75 words):

Summary of how this work contributes to your project ( c 75 words):

Brief description of the implications of this work ( c 25 words):

Identify any gap or controversy in knowledge this work points up, and how your project could address those problems ( c 50 words):

Exercise 2: Towards an analysis

Develop a short statement ( c 250 words) about the kind of data that would be useful to address your research question, and how you’d analyse it. Some questions to consider in writing this statement include:

• What are the central concepts or variables in your project? Offer a brief definition of each.
• Do any data sources exist on those concepts or variables, or would you need to collect data?
• Of the analytical strategies you could apply to that data, which would be the most appropriate to answer your question? Which would be the most feasible for you? Consider at least two methods, noting their advantages or disadvantages for your project.

Links & books

One of the best texts ever written about planning and executing research comes from a source that might be unexpected: a 60-year-old work on urban planning by a self-trained scholar. The classic book The Death and Life of Great American Cities (1961) by Jane Jacobs (available complete and free of charge via this link ) is worth reading in its entirety just for the pleasure of it. But the final 20 pages – a concluding chapter titled ‘The Kind of Problem a City Is’ – are really about the process of thinking through and investigating a problem. Highly recommended as a window into the craft of research.

Jacobs’s text references an essay on advancing human knowledge by the mathematician Warren Weaver. At the time, Weaver was director of the Rockefeller Foundation, in charge of funding basic research in the natural and medical sciences. Although the essay is titled ‘A Quarter Century in the Natural Sciences’ (1960) and appears at first blush to be merely a summation of one man’s career, it turns out to be something much bigger and more interesting: a meditation on the history of human beings seeking answers to big questions about the world. Weaver goes back to the 17th century to trace the origins of systematic research thinking, with enthusiasm and vivid anecdotes that make the process come alive. The essay is worth reading in its entirety, and is available free of charge via this link .

For those seeking a more in-depth, professional-level discussion of the logic of research design, the political scientist Harvey Starr provides insight in a compact format in the article ‘Cumulation from Proper Specification: Theory, Logic, Research Design, and “Nice” Laws’ (2005). Starr reviews the ‘research triad’, consisting of the interlinked considerations of formulating a question, selecting relevant theories and applying appropriate methods. The full text of the article, published in the scholarly journal Conflict Management and Peace Science , is available, free of charge, via this link .

Finally, the book Getting What You Came For (1992) by Robert Peters is not only an outstanding guide for anyone contemplating graduate school – from the application process onward – but it also includes several excellent chapters on planning and executing research, applicable across a wide variety of subject areas. It was an invaluable resource for me 25 years ago, and it remains in print with good reason; I recommend it to all my students, particularly Chapter 16 (‘The Thesis Topic: Finding It’), Chapter 17 (‘The Thesis Proposal’) and Chapter 18 (‘The Thesis: Writing It’).

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by Lucia Tecuta

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Planning Research

Once working from a research paradigm it becomes possible to start making concrete choices about method(s). Depending on the project, this will involve choices about things like:

• Who will be involved? How will they be selected/contacted?
• How data will be collected
• How data will be managed and stored securely
• Designing, producing and piloting research instruments
• Determining the basis of rigour in the study and the “trustworthiness”(credibility, transferability, dependability, and confirmability) of the data(Guba, 1981; Shento, 2004)
• Ensuring ethical good practice is built into the project (see below)
• Setting a plan for data analysis

The data collection phase can begin once these decisions are made. It can be very tempting to start collecting data as soon as possible in the research process as this gives a sense of progress. However, it is usually worth getting things exactly right before collecting data as an error found in your approach further down the line can be harder to correct or recalibrate around. From here, things become a bit less generic as the specifics of data collection and analysis are going to be determined by the research methods being used. There are additional aspects which it is worth considering in detail at the research design stage.

Research Methods Handbook Copyright © 2020 by Rob Farrow; Francisco Iniesto; Martin Weller; and Rebecca Pitt is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Research Methods Guide: Research Design & Method

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FAQ: Research Design & Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal.  It depends on what subjects (and who) you want to study.  Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus.  To answer these questions, you need to make a decision about how to collect your data.  Most frequently used methods include:

• Observation / Participant Observation
• Focus Groups
• Experiments
• Secondary Data Analysis / Archival Study
• Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity.   For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider.  An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time.  Using a survey helps you collect more data quickly, yet it may lack details.  So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

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Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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2.2 Research Methods

Learning objectives.

By the end of this section, you should be able to:

• Recall the 6 Steps of the Scientific Method
• Differentiate between four kinds of research methods: surveys, field research, experiments, and secondary data analysis.
• Explain the appropriateness of specific research approaches for specific topics.

Sociologists examine the social world, see a problem or interesting pattern, and set out to study it. They use research methods to design a study. Planning the research design is a key step in any sociological study. Sociologists generally choose from widely used methods of social investigation: primary source data collection such as survey, participant observation, ethnography, case study, unobtrusive observations, experiment, and secondary data analysis , or use of existing sources. Every research method comes with plusses and minuses, and the topic of study strongly influences which method or methods are put to use. When you are conducting research think about the best way to gather or obtain knowledge about your topic, think of yourself as an architect. An architect needs a blueprint to build a house, as a sociologist your blueprint is your research design including your data collection method.

When entering a particular social environment, a researcher must be careful. There are times to remain anonymous and times to be overt. There are times to conduct interviews and times to simply observe. Some participants need to be thoroughly informed; others should not know they are being observed. A researcher wouldn’t stroll into a crime-ridden neighborhood at midnight, calling out, “Any gang members around?”

Making sociologists’ presence invisible is not always realistic for other reasons. That option is not available to a researcher studying prison behaviors, early education, or the Ku Klux Klan. Researchers can’t just stroll into prisons, kindergarten classrooms, or Klan meetings and unobtrusively observe behaviors or attract attention. In situations like these, other methods are needed. Researchers choose methods that best suit their study topics, protect research participants or subjects, and that fit with their overall approaches to research.

As a research method, a survey collects data from subjects who respond to a series of questions about behaviors and opinions, often in the form of a questionnaire or an interview. The survey is one of the most widely used scientific research methods. The standard survey format allows individuals a level of anonymity in which they can express personal ideas.

At some point, most people in the United States respond to some type of survey. The 2020 U.S. Census is an excellent example of a large-scale survey intended to gather sociological data. Since 1790, United States has conducted a survey consisting of six questions to received demographical data pertaining to residents. The questions pertain to the demographics of the residents who live in the United States. Currently, the Census is received by residents in the United Stated and five territories and consists of 12 questions.

Not all surveys are considered sociological research, however, and many surveys people commonly encounter focus on identifying marketing needs and strategies rather than testing a hypothesis or contributing to social science knowledge. Questions such as, “How many hot dogs do you eat in a month?” or “Were the staff helpful?” are not usually designed as scientific research. The Nielsen Ratings determine the popularity of television programming through scientific market research. However, polls conducted by television programs such as American Idol or So You Think You Can Dance cannot be generalized, because they are administered to an unrepresentative population, a specific show’s audience. You might receive polls through your cell phones or emails, from grocery stores, restaurants, and retail stores. They often provide you incentives for completing the survey.

Sociologists conduct surveys under controlled conditions for specific purposes. Surveys gather different types of information from people. While surveys are not great at capturing the ways people really behave in social situations, they are a great method for discovering how people feel, think, and act—or at least how they say they feel, think, and act. Surveys can track preferences for presidential candidates or reported individual behaviors (such as sleeping, driving, or texting habits) or information such as employment status, income, and education levels.

A survey targets a specific population , people who are the focus of a study, such as college athletes, international students, or teenagers living with type 1 (juvenile-onset) diabetes. Most researchers choose to survey a small sector of the population, or a sample , a manageable number of subjects who represent a larger population. The success of a study depends on how well a population is represented by the sample. In a random sample , every person in a population has the same chance of being chosen for the study. As a result, a Gallup Poll, if conducted as a nationwide random sampling, should be able to provide an accurate estimate of public opinion whether it contacts 2,000 or 10,000 people.

After selecting subjects, the researcher develops a specific plan to ask questions and record responses. It is important to inform subjects of the nature and purpose of the survey up front. If they agree to participate, researchers thank subjects and offer them a chance to see the results of the study if they are interested. The researcher presents the subjects with an instrument, which is a means of gathering the information.

A common instrument is a questionnaire. Subjects often answer a series of closed-ended questions . The researcher might ask yes-or-no or multiple-choice questions, allowing subjects to choose possible responses to each question. This kind of questionnaire collects quantitative data —data in numerical form that can be counted and statistically analyzed. Just count up the number of “yes” and “no” responses or correct answers, and chart them into percentages.

Questionnaires can also ask more complex questions with more complex answers—beyond “yes,” “no,” or checkbox options. These types of inquiries use open-ended questions that require short essay responses. Participants willing to take the time to write those answers might convey personal religious beliefs, political views, goals, or morals. The answers are subjective and vary from person to person. How do you plan to use your college education?

Some topics that investigate internal thought processes are impossible to observe directly and are difficult to discuss honestly in a public forum. People are more likely to share honest answers if they can respond to questions anonymously. This type of personal explanation is qualitative data —conveyed through words. Qualitative information is harder to organize and tabulate. The researcher will end up with a wide range of responses, some of which may be surprising. The benefit of written opinions, though, is the wealth of in-depth material that they provide.

An interview is a one-on-one conversation between the researcher and the subject, and it is a way of conducting surveys on a topic. However, participants are free to respond as they wish, without being limited by predetermined choices. In the back-and-forth conversation of an interview, a researcher can ask for clarification, spend more time on a subtopic, or ask additional questions. In an interview, a subject will ideally feel free to open up and answer questions that are often complex. There are no right or wrong answers. The subject might not even know how to answer the questions honestly.

Questions such as “How does society’s view of alcohol consumption influence your decision whether or not to take your first sip of alcohol?” or “Did you feel that the divorce of your parents would put a social stigma on your family?” involve so many factors that the answers are difficult to categorize. A researcher needs to avoid steering or prompting the subject to respond in a specific way; otherwise, the results will prove to be unreliable. The researcher will also benefit from gaining a subject’s trust, from empathizing or commiserating with a subject, and from listening without judgment.

Surveys often collect both quantitative and qualitative data. For example, a researcher interviewing people who are incarcerated might receive quantitative data, such as demographics – race, age, sex, that can be analyzed statistically. For example, the researcher might discover that 20 percent of incarcerated people are above the age of 50. The researcher might also collect qualitative data, such as why people take advantage of educational opportunities during their sentence and other explanatory information.

The survey can be carried out online, over the phone, by mail, or face-to-face. When researchers collect data outside a laboratory, library, or workplace setting, they are conducting field research, which is our next topic.

Field Research

The work of sociology rarely happens in limited, confined spaces. Rather, sociologists go out into the world. They meet subjects where they live, work, and play. Field research refers to gathering primary data from a natural environment. To conduct field research, the sociologist must be willing to step into new environments and observe, participate, or experience those worlds. In field work, the sociologists, rather than the subjects, are the ones out of their element.

The researcher interacts with or observes people and gathers data along the way. The key point in field research is that it takes place in the subject’s natural environment, whether it’s a coffee shop or tribal village, a homeless shelter or the DMV, a hospital, airport, mall, or beach resort.

While field research often begins in a specific setting , the study’s purpose is to observe specific behaviors in that setting. Field work is optimal for observing how people think and behave. It seeks to understand why they behave that way. However, researchers may struggle to narrow down cause and effect when there are so many variables floating around in a natural environment. And while field research looks for correlation, its small sample size does not allow for establishing a causal relationship between two variables. Indeed, much of the data gathered in sociology do not identify a cause and effect but a correlation .

Sociology in the Real World

Beyoncé and lady gaga as sociological subjects.

Sociologists have studied Lady Gaga and Beyoncé and their impact on music, movies, social media, fan participation, and social equality. In their studies, researchers have used several research methods including secondary analysis, participant observation, and surveys from concert participants.

In their study, Click, Lee & Holiday (2013) interviewed 45 Lady Gaga fans who utilized social media to communicate with the artist. These fans viewed Lady Gaga as a mirror of themselves and a source of inspiration. Like her, they embrace not being a part of mainstream culture. Many of Lady Gaga’s fans are members of the LGBTQ community. They see the “song “Born This Way” as a rallying cry and answer her calls for “Paws Up” with a physical expression of solidarity—outstretched arms and fingers bent and curled to resemble monster claws.”

Sascha Buchanan (2019) made use of participant observation to study the relationship between two fan groups, that of Beyoncé and that of Rihanna. She observed award shows sponsored by iHeartRadio, MTV EMA, and BET that pit one group against another as they competed for Best Fan Army, Biggest Fans, and FANdemonium. Buchanan argues that the media thus sustains a myth of rivalry between the two most commercially successful Black women vocal artists.

Participant Observation

In 2000, a comic writer named Rodney Rothman wanted an insider’s view of white-collar work. He slipped into the sterile, high-rise offices of a New York “dot com” agency. Every day for two weeks, he pretended to work there. His main purpose was simply to see whether anyone would notice him or challenge his presence. No one did. The receptionist greeted him. The employees smiled and said good morning. Rothman was accepted as part of the team. He even went so far as to claim a desk, inform the receptionist of his whereabouts, and attend a meeting. He published an article about his experience in The New Yorker called “My Fake Job” (2000). Later, he was discredited for allegedly fabricating some details of the story and The New Yorker issued an apology. However, Rothman’s entertaining article still offered fascinating descriptions of the inside workings of a “dot com” company and exemplified the lengths to which a writer, or a sociologist, will go to uncover material.

Rothman had conducted a form of study called participant observation , in which researchers join people and participate in a group’s routine activities for the purpose of observing them within that context. This method lets researchers experience a specific aspect of social life. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behavior. A researcher might work as a waitress in a diner, experience homelessness for several weeks, or ride along with police officers as they patrol their regular beat. Often, these researchers try to blend in seamlessly with the population they study, and they may not disclose their true identity or purpose if they feel it would compromise the results of their research.

At the beginning of a field study, researchers might have a question: “What really goes on in the kitchen of the most popular diner on campus?” or “What is it like to be homeless?” Participant observation is a useful method if the researcher wants to explore a certain environment from the inside.

Field researchers simply want to observe and learn. In such a setting, the researcher will be alert and open minded to whatever happens, recording all observations accurately. Soon, as patterns emerge, questions will become more specific, observations will lead to hypotheses, and hypotheses will guide the researcher in analyzing data and generating results.

In a study of small towns in the United States conducted by sociological researchers John S. Lynd and Helen Merrell Lynd, the team altered their purpose as they gathered data. They initially planned to focus their study on the role of religion in U.S. towns. As they gathered observations, they realized that the effect of industrialization and urbanization was the more relevant topic of this social group. The Lynds did not change their methods, but they revised the purpose of their study.

This shaped the structure of Middletown: A Study in Modern American Culture , their published results (Lynd & Lynd, 1929).

The Lynds were upfront about their mission. The townspeople of Muncie, Indiana, knew why the researchers were in their midst. But some sociologists prefer not to alert people to their presence. The main advantage of covert participant observation is that it allows the researcher access to authentic, natural behaviors of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ behavior. Becoming an inside member of a group, organization, or subculture takes time and effort. Researchers must pretend to be something they are not. The process could involve role playing, making contacts, networking, or applying for a job.

Once inside a group, some researchers spend months or even years pretending to be one of the people they are observing. However, as observers, they cannot get too involved. They must keep their purpose in mind and apply the sociological perspective. That way, they illuminate social patterns that are often unrecognized. Because information gathered during participant observation is mostly qualitative, rather than quantitative, the end results are often descriptive or interpretive. The researcher might present findings in an article or book and describe what he or she witnessed and experienced.

This type of research is what journalist Barbara Ehrenreich conducted for her book Nickel and Dimed . One day over lunch with her editor, Ehrenreich mentioned an idea. How can people exist on minimum-wage work? How do low-income workers get by? she wondered. Someone should do a study . To her surprise, her editor responded, Why don’t you do it?

That’s how Ehrenreich found herself joining the ranks of the working class. For several months, she left her comfortable home and lived and worked among people who lacked, for the most part, higher education and marketable job skills. Undercover, she applied for and worked minimum wage jobs as a waitress, a cleaning woman, a nursing home aide, and a retail chain employee. During her participant observation, she used only her income from those jobs to pay for food, clothing, transportation, and shelter.

She discovered the obvious, that it’s almost impossible to get by on minimum wage work. She also experienced and observed attitudes many middle and upper-class people never think about. She witnessed firsthand the treatment of working class employees. She saw the extreme measures people take to make ends meet and to survive. She described fellow employees who held two or three jobs, worked seven days a week, lived in cars, could not pay to treat chronic health conditions, got randomly fired, submitted to drug tests, and moved in and out of homeless shelters. She brought aspects of that life to light, describing difficult working conditions and the poor treatment that low-wage workers suffer.

The book she wrote upon her return to her real life as a well-paid writer, has been widely read and used in many college classrooms.

Ethnography

Ethnography is the immersion of the researcher in the natural setting of an entire social community to observe and experience their everyday life and culture. The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a social group.

An ethnographic study might observe, for example, a small U.S. fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or an amusement park. These places all have borders. People live, work, study, or vacation within those borders. People are there for a certain reason and therefore behave in certain ways and respect certain cultural norms. An ethnographer would commit to spending a determined amount of time studying every aspect of the chosen place, taking in as much as possible.

A sociologist studying a tribe in the Amazon might watch the way villagers go about their daily lives and then write a paper about it. To observe a spiritual retreat center, an ethnographer might sign up for a retreat and attend as a guest for an extended stay, observe and record data, and collate the material into results.

Institutional Ethnography

Institutional ethnography is an extension of basic ethnographic research principles that focuses intentionally on everyday concrete social relationships. Developed by Canadian sociologist Dorothy E. Smith (1990), institutional ethnography is often considered a feminist-inspired approach to social analysis and primarily considers women’s experiences within male- dominated societies and power structures. Smith’s work is seen to challenge sociology’s exclusion of women, both academically and in the study of women’s lives (Fenstermaker, n.d.).

Historically, social science research tended to objectify women and ignore their experiences except as viewed from the male perspective. Modern feminists note that describing women, and other marginalized groups, as subordinates helps those in authority maintain their own dominant positions (Social Sciences and Humanities Research Council of Canada n.d.). Smith’s three major works explored what she called “the conceptual practices of power” and are still considered seminal works in feminist theory and ethnography (Fensternmaker n.d.).

Sociological Research

The making of middletown: a study in modern u.s. culture.

In 1924, a young married couple named Robert and Helen Lynd undertook an unprecedented ethnography: to apply sociological methods to the study of one U.S. city in order to discover what “ordinary” people in the United States did and believed. Choosing Muncie, Indiana (population about 30,000) as their subject, they moved to the small town and lived there for eighteen months.

Ethnographers had been examining other cultures for decades—groups considered minorities or outsiders—like gangs, immigrants, and the poor. But no one had studied the so-called average American.

Recording interviews and using surveys to gather data, the Lynds objectively described what they observed. Researching existing sources, they compared Muncie in 1890 to the Muncie they observed in 1924. Most Muncie adults, they found, had grown up on farms but now lived in homes inside the city. As a result, the Lynds focused their study on the impact of industrialization and urbanization.

They observed that Muncie was divided into business and working class groups. They defined business class as dealing with abstract concepts and symbols, while working class people used tools to create concrete objects. The two classes led different lives with different goals and hopes. However, the Lynds observed, mass production offered both classes the same amenities. Like wealthy families, the working class was now able to own radios, cars, washing machines, telephones, vacuum cleaners, and refrigerators. This was an emerging material reality of the 1920s.

As the Lynds worked, they divided their manuscript into six chapters: Getting a Living, Making a Home, Training the Young, Using Leisure, Engaging in Religious Practices, and Engaging in Community Activities.

When the study was completed, the Lynds encountered a big problem. The Rockefeller Foundation, which had commissioned the book, claimed it was useless and refused to publish it. The Lynds asked if they could seek a publisher themselves.

Middletown: A Study in Modern American Culture was not only published in 1929 but also became an instant bestseller, a status unheard of for a sociological study. The book sold out six printings in its first year of publication, and has never gone out of print (Caplow, Hicks, & Wattenberg. 2000).

Nothing like it had ever been done before. Middletown was reviewed on the front page of the New York Times. Readers in the 1920s and 1930s identified with the citizens of Muncie, Indiana, but they were equally fascinated by the sociological methods and the use of scientific data to define ordinary people in the United States. The book was proof that social data was important—and interesting—to the U.S. public.

Sometimes a researcher wants to study one specific person or event. A case study is an in-depth analysis of a single event, situation, or individual. To conduct a case study, a researcher examines existing sources like documents and archival records, conducts interviews, engages in direct observation and even participant observation, if possible.

Researchers might use this method to study a single case of a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study as a method is that while offering depth on a topic, it does not provide enough evidence to form a generalized conclusion. In other words, it is difficult to make universal claims based on just one person, since one person does not verify a pattern. This is why most sociologists do not use case studies as a primary research method.

However, case studies are useful when the single case is unique. In these instances, a single case study can contribute tremendous insight. For example, a feral child, also called “wild child,” is one who grows up isolated from human beings. Feral children grow up without social contact and language, which are elements crucial to a “civilized” child’s development. These children mimic the behaviors and movements of animals, and often invent their own language. There are only about one hundred cases of “feral children” in the world.

As you may imagine, a feral child is a subject of great interest to researchers. Feral children provide unique information about child development because they have grown up outside of the parameters of “normal” growth and nurturing. And since there are very few feral children, the case study is the most appropriate method for researchers to use in studying the subject.

At age three, a Ukranian girl named Oxana Malaya suffered severe parental neglect. She lived in a shed with dogs, and she ate raw meat and scraps. Five years later, a neighbor called authorities and reported seeing a girl who ran on all fours, barking. Officials brought Oxana into society, where she was cared for and taught some human behaviors, but she never became fully socialized. She has been designated as unable to support herself and now lives in a mental institution (Grice 2011). Case studies like this offer a way for sociologists to collect data that may not be obtained by any other method.

Experiments

You have probably tested some of your own personal social theories. “If I study at night and review in the morning, I’ll improve my retention skills.” Or, “If I stop drinking soda, I’ll feel better.” Cause and effect. If this, then that. When you test the theory, your results either prove or disprove your hypothesis.

One way researchers test social theories is by conducting an experiment , meaning they investigate relationships to test a hypothesis—a scientific approach.

There are two main types of experiments: lab-based experiments and natural or field experiments. In a lab setting, the research can be controlled so that more data can be recorded in a limited amount of time. In a natural or field- based experiment, the time it takes to gather the data cannot be controlled but the information might be considered more accurate since it was collected without interference or intervention by the researcher.

As a research method, either type of sociological experiment is useful for testing if-then statements: if a particular thing happens (cause), then another particular thing will result (effect). To set up a lab-based experiment, sociologists create artificial situations that allow them to manipulate variables.

Classically, the sociologist selects a set of people with similar characteristics, such as age, class, race, or education. Those people are divided into two groups. One is the experimental group and the other is the control group. The experimental group is exposed to the independent variable(s) and the control group is not. To test the benefits of tutoring, for example, the sociologist might provide tutoring to the experimental group of students but not to the control group. Then both groups would be tested for differences in performance to see if tutoring had an effect on the experimental group of students. As you can imagine, in a case like this, the researcher would not want to jeopardize the accomplishments of either group of students, so the setting would be somewhat artificial. The test would not be for a grade reflected on their permanent record of a student, for example.

And if a researcher told the students they would be observed as part of a study on measuring the effectiveness of tutoring, the students might not behave naturally. This is called the Hawthorne effect —which occurs when people change their behavior because they know they are being watched as part of a study. The Hawthorne effect is unavoidable in some research studies because sociologists have to make the purpose of the study known. Subjects must be aware that they are being observed, and a certain amount of artificiality may result (Sonnenfeld 1985).

A real-life example will help illustrate the process. In 1971, Frances Heussenstamm, a sociology professor at California State University at Los Angeles, had a theory about police prejudice. To test her theory, she conducted research. She chose fifteen students from three ethnic backgrounds: Black, White, and Hispanic. She chose students who routinely drove to and from campus along Los Angeles freeway routes, and who had had perfect driving records for longer than a year.

Next, she placed a Black Panther bumper sticker on each car. That sticker, a representation of a social value, was the independent variable. In the 1970s, the Black Panthers were a revolutionary group actively fighting racism. Heussenstamm asked the students to follow their normal driving patterns. She wanted to see whether seeming support for the Black Panthers would change how these good drivers were treated by the police patrolling the highways. The dependent variable would be the number of traffic stops/citations.

The first arrest, for an incorrect lane change, was made two hours after the experiment began. One participant was pulled over three times in three days. He quit the study. After seventeen days, the fifteen drivers had collected a total of thirty-three traffic citations. The research was halted. The funding to pay traffic fines had run out, and so had the enthusiasm of the participants (Heussenstamm, 1971).

Secondary Data Analysis

While sociologists often engage in original research studies, they also contribute knowledge to the discipline through secondary data analysis . Secondary data does not result from firsthand research collected from primary sources, but are the already completed work of other researchers or data collected by an agency or organization. Sociologists might study works written by historians, economists, teachers, or early sociologists. They might search through periodicals, newspapers, or magazines, or organizational data from any period in history.

Using available information not only saves time and money but can also add depth to a study. Sociologists often interpret findings in a new way, a way that was not part of an author’s original purpose or intention. To study how women were encouraged to act and behave in the 1960s, for example, a researcher might watch movies, televisions shows, and situation comedies from that period. Or to research changes in behavior and attitudes due to the emergence of television in the late 1950s and early 1960s, a sociologist would rely on new interpretations of secondary data. Decades from now, researchers will most likely conduct similar studies on the advent of mobile phones, the Internet, or social media.

Social scientists also learn by analyzing the research of a variety of agencies. Governmental departments and global groups, like the U.S. Bureau of Labor Statistics or the World Health Organization (WHO), publish studies with findings that are useful to sociologists. A public statistic like the foreclosure rate might be useful for studying the effects of a recession. A racial demographic profile might be compared with data on education funding to examine the resources accessible by different groups.

One of the advantages of secondary data like old movies or WHO statistics is that it is nonreactive research (or unobtrusive research), meaning that it does not involve direct contact with subjects and will not alter or influence people’s behaviors. Unlike studies requiring direct contact with people, using previously published data does not require entering a population and the investment and risks inherent in that research process.

Using available data does have its challenges. Public records are not always easy to access. A researcher will need to do some legwork to track them down and gain access to records. To guide the search through a vast library of materials and avoid wasting time reading unrelated sources, sociologists employ content analysis , applying a systematic approach to record and value information gleaned from secondary data as they relate to the study at hand.

Also, in some cases, there is no way to verify the accuracy of existing data. It is easy to count how many drunk drivers, for example, are pulled over by the police. But how many are not? While it’s possible to discover the percentage of teenage students who drop out of high school, it might be more challenging to determine the number who return to school or get their GED later.

Another problem arises when data are unavailable in the exact form needed or do not survey the topic from the precise angle the researcher seeks. For example, the average salaries paid to professors at a public school is public record. But these figures do not necessarily reveal how long it took each professor to reach the salary range, what their educational backgrounds are, or how long they’ve been teaching.

When conducting content analysis, it is important to consider the date of publication of an existing source and to take into account attitudes and common cultural ideals that may have influenced the research. For example, when Robert S. Lynd and Helen Merrell Lynd gathered research in the 1920s, attitudes and cultural norms were vastly different then than they are now. Beliefs about gender roles, race, education, and work have changed significantly since then. At the time, the study’s purpose was to reveal insights about small U.S. communities. Today, it is an illustration of 1920s attitudes and values.

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• Research Data Lifecycle Guide

Developing a Data Management Plan

This section breaks down different topics required for the planning and preparation of data used in research at Case Western Reserve University. In this phase you should understand the research being conducted, the type and methods used for collecting data, the methods used to prepare and analyze the data, addressing budgets and resources required, and have a sound understanding of how you will manage data activities during your research project.

Many federal sponsors of Case Western Reserve funded research have required data sharing plans in research proposals since 2003. As of Jan. 25, 2023, the National Institutes of Health has revised its data management and sharing requirements. 

This website is designed to provide basic information and best practices to seasoned and new investigators as well as detailed guidance for adhering to the revised NIH policy.  

Basics of Research Data Management

What is research data management?

Research data management (RDM) comprises a set of best practices that include file organization, documentation, storage, backup, security, preservation, and sharing, which affords researchers the ability to more quickly, efficiently, and accurately find, access, and understand their own or others' research data.

Why should you care about research data management?

RDM practices, if applied consistently and as early in a project as possible, can save you considerable time and effort later, when specific data are needed, when others need to make sense of your data, or when you decide to share or otherwise upload your data to a digital repository. Adopting RDM practices will also help you more easily comply with the data management plan (DMP) required for obtaining grants from many funding agencies and institutions.

Does data need to be retained after a project is completed?

Research data must be retained in sufficient detail and for an adequate period of time to enable appropriate responses to questions about accuracy, authenticity, primacy and compliance with laws and regulations governing the conduct of the research. External funding agencies will each have different requirements regarding storage, retention, and availability of research data. Please carefully review your award or agreement for the disposition of data requirements and data retention policies.

A good data management plan begins by understanding the sponsor requirements funding your research. As a principal investigator (PI) it is your responsibility to be knowledgeable of sponsors requirements. The Data Management Plan Tool (DMPTool) has been designed to help PIs adhere to sponsor requirements efficiently and effectively. It is strongly recommended that you take advantage of the DMPTool.  

CWRU has an institutional account with DMPTool that enables users to access all of its resources via your Single Sign On credentials. CWRU's DMPTool account is supported by members of the Digital Scholarship team with the Freedman Center for Digital Scholarship. Please use the RDM Intake Request form to schedule a consultation if you would like support or guidance regarding developing a Data Management Plan.

Some basic steps to get started:

• Sign into the  DMPTool site  to start creating a DMP for managing and sharing your data. 
• On the DMPTool site, you can find the most up to date templates for creating a DMP for a long list of funders, including the NIH, NEH, NSF, and more. 
• Explore sample DMPs to see examples of successful plans .

Be sure that your DMP is addressing any and all federal and/or funder requirements and associated DMP templates that may apply to your project. It is strongly recommended that investigators submitting proposals to the NIH utilize this tool. 

The NIH is mandating Data Management and Sharing Plans for all proposals submitted after Jan. 25, 2023.  Guidance for completing a NIH Data Management Plan has its own dedicated content to provide investigators detailed guidance on development of these plans for inclusion in proposals. 

A Data Management Plan can help create and maintain reliable data and promote project success. DMPs, when carefully constructed and reliably adhered to, help guide elements of your research and data organization.

A DMP can help you:

Document your process and data.

• Maintain a file with information on researchers and collaborators and their roles, sponsors/funding sources, methods/techniques/protocols/standards used, instrumentation, software (w/versions), references used, any applicable restrictions on its distribution or use.
• Establish how you will document file changes, name changes, dates of changes, etc. Where will you record of these changes? Try to keep this sort of information in a plain text file located in the same folder as the files to which it pertains.
• How are derived data products created? A DMP encourages consistent description of data processing performed, software (including version number) used, and analyses applied to data.
• Establish regular forms or templates for data collection. This helps reduce gaps in your data, promotes consistency throughout the project.

Explain your data

• From the outset, consider why your data were collected, what the known and expected conditions may be for collection, and information such as time and place, resolution, and standards of data collected.
• What attributes, fields, or parameters will be studied and included in your data files? Identify and describe these in each file that employs them.
• For an overview of data dictionaries, see the USGS page here: https://www.usgs.gov/products/data-and-tools/data-management/data-dictionaries

DMP Requirements

Why are you being asked to include a data management plan (DMP) in your grant application? For grants awarded by US governmental agencies, two federal memos from the US Office of Science and Technology Policy (OSTP), issued in 2013 and 2015 , respectively, have prompted this requirement. These memos mandate public access to federally- (and, thus, taxpayer-) funded research results, reflecting a commitment by the government to greater accountability and transparency. While "results" generally refers to the publications and reports produced from a research project, it is increasingly used to refer to the resulting data as well.

Federal research-funding agencies  have responded to the OSTP memos by issuing their own guidelines and requirements for grant applicants (see below), specifying whether and how research data in particular are to be managed in order to be publicly and properly accessible.

• NSF—National Science Foundation "Proposals submitted or due on or after January 18, 2011, must include a supplementary document of no more than two pages labeled 'Data Management Plan'. This supplementary document should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results." Note: Additional requirements may apply per Directorate, Office, Division, Program, or other NSF unit.
• NIH—National Institutes of Health "To facilitate data sharing, investigators submitting a research application requesting $500,000 or more of direct costs in any single year to NIH on or after October 1, 2003 are expected to include a plan for sharing final research data for research purposes, or state why data sharing is not possible."
• NASA—National Aeronautics and Space Administration "The purpose of a Data Management Plan (DMP) is to address the management of data from Earth science missions, from the time of their data collection/observation, to their entry into permanent archives."
• DOD—Department of Defense "A Data Management Plan (DMP) describing the scientific data expected to be created or gathered in the course of a research project must be submitted to DTIC at the start of each research effort. It is important that DoD researchers document plans for preserving data at the outset, keeping in mind the potential utility of the data for future research or to support transition to operational or other environments. Otherwise, the data is lost as researchers move on to other efforts. The essential descriptive elements of the DMP are listed in section 3 of DoDI 3200.12, although the format of the plan may be adjusted to conform to standards established by the relevant scientific discipline or one that meets the requirements of the responsible Component"
• Department of Education "The purpose of this document is to describe the implementation of this policy on public access to data and to provide guidance to applicants for preparing the Data Management Plan (DMP) that must outline data sharing and be submitted with the grant application. The DMP should describe a plan to provide discoverable and citable dataset(s) with sufficient documentation to support responsible use by other researchers, and should address four interrelated concerns—access, permissions, documentation, and resources—which must be considered in the earliest stages of planning for the grant."
• " Office of Scientific and Technical Information (OSTI) Provides access to free, publicly-available research sponsored by the Department of Energy (DOE), including technical reports, bibliographic citations, journal articles, conference papers, books, multimedia, software, and data.

Data Management Best Practices

As you plan to collect data for research, keep in mind the following best practices. 

Keep Your Data Accessible to You

• Store your temporary working files somewhere easily accessible, like on a local hard drive or shared server.
• While cloud storage is a convenient solution for storage and sharing, there are often concerns about data privacy and preservation. Be sure to only put data in the cloud that you are comfortable with and that your funding and/or departmental requirements allow.
• For long-term storage, data should be put into preservation systems that are well-managed. [U]Tech provides several long-term data storage options for cloud and campus. 
• Don't keep your original data on a thumb drive or portable hard drive, as it can be easily lost or stolen.
• Think about file formats that have a long life and that are readable by many programs. Formats like ascii, .txt, .csv, .pdf are great for long term  preservation.
• A DMP is not a replacement for good data management practices, but it can set you on the right path if it is consistently followed. Consistently revisit your plan to ensure you are following it and adhering to funder requirements.

Preservation

• Know the difference between storing and preserving your data. True preservation is the ongoing process of making sure your data are secure and accessible for future generations. Many sponsors have preferred or recommended data repositories. The DMP tool can help you identify these preferred repositories. 
• Identify data with long-term value. Preserve the raw data and any intermediate/derived products that are expensive to reproduce or can be directly used for analysis. Preserve any scripted code that was used to clean and transform the data.
• Whenever converting your data from one format to another, keep a copy of the original file and format to avoid loss or corruption of your important files.
• Leverage online platforms like OSF can help your group organize, version, share, and preserve your data, if the sponsor hasn’t specified a specific platform.
• Adhere to federal sponsor requirements on utilizing accepted data repositories (NIH dbGaP, NIH SRA, NIH CRDC, etc.) for preservation. 

Backup, Backup, Backup

• The general rule is to keep 3 copies of your data: 2 copies onsite, 1 offsite.
• Backup your data regularly and frequently - automate the process if possible. This may mean weekly duplication of your working files to a separate drive, syncing your folders to a cloud service like Box, or dedicating a block of time every week to ensure you've copied everything to another location.

Organization

• Establish a consistent, descriptive filing system that is intelligible to future researchers and does not rely on your own inside knowledge of your research.
• A descriptive directory and file-naming structure should guide users through the contents to help them find whatever they are looking for.

Naming Conventions

• Use consistent, descriptive filenames that reliably indicate the contents of the file.
• If your discipline requires or recommends particular naming conventions, use them!
• Do not use spaces between words. Use either camelcase or underscores to separate words
• Include LastnameFirstname descriptors where appropriate.
• Avoid using MM-DD-YYYY formats
• Do not append vague descriptors like "latest" or "final" to your file versions. Instead, append the version's date or a consistently iterated version number.

Clean Your Data

• Mistakes happen, and often researchers don't notice at first. If you are manually entering data, be sure to double-check the entries for consistency and duplication. Often having a fresh set of eyes will help to catch errors before they become problems.
• Tabular data can often be error checked by sorting the fields alphanumerically to catch simple typos, extra spaces, or otherwise extreme outliers. Be sure to save your data before sorting it to ensure you do not disrupt the records!
• Programs like OpenRefine  are useful for checking for consistency in coding for records and variables, catching missing values, transforming data, and much more.

What should you do if you need assistance implementing RDM practices?

Whether it's because you need discipline-specific metadata standards for your data, help with securing sensitive data, or assistance writing a data management plan for a grant, help is available to you at CWRU. In addition to consulting the resources featured in this guide, you are encouraged to contact your department's liaison librarian.

If you are planning to submit a research proposal and need assistance with budgeting for data storage and or applications used to capture, manage, and or process data UTech provides information and assistance including resource boilerplates that list what centralized resources are available. 

More specific guidance for including a budget for Data Management and Sharing is included on this document: Budgeting for Data Management and Sharing . 

Custody of Research Data

The PI is the custodian of research data, unless agreed on in writing otherwise and the agreement is on file with the University, and is responsible for the collection, management, and retention of research data. The PI should adopt an orderly system of data organization and should communicate the chosen system to all members of a research group and to the appropriate administrative personnel, where applicable. Particularly for long-term research projects, the PI should establish and maintain procedures for the protection and management of essential records.

CWRU Custody of Research Data Policy  

Data Sharing

Many funding agencies require data to be shared for the purposes of reproducibility and other important scientific goals. It is important to plan for the timely release and sharing of final research data for use by other researchers.  The final release of data should be included as a key deliverable of the DMP. Knowledge of the discipline-specific database, data repository, data enclave, or archive store used to disseminate the data should also be documented as needed. 

The NIH is mandating Data Management and Sharing Plans for all proposals submitted after Jan. 25, 2023. Guidance for completing a NIH Data Management and Sharing Plan  has its own dedicated content to provide investigators detailed guidance on development of these plans for inclusion in proposals.

Analytic Methods of Urban Planning: Quantitative [Module 2]

This course introduces students to quantitative analysis and research methods for urban planning. The course begins with an examination of how quantitative methods fit within the broader analytic landscape. It then exposes students to basic descriptive statistics (including measures of central tendency and dispersion), principles of statistical inference, and a wide variety of analytic methods and their practical application. By the end of the course, students will be comfortable with many analytic techniques relevant to urban planning and policy, including: z-tests, t-tests, ANOVA, chi square tests, correlation, and multivariate regression. On a broader level, students will gain the ability to understand and critically question the kinds of analyses and representations of quantitative data encountered in urban planning and allied disciplines.

The aim of the course is to introduce students to key concepts and tools in quantitative analysis and research. Most importantly, however, the goal is to develop students’ intuition regarding data analysis and the application of statistical techniques. By the end of the course, students will be familiar with how common techniques of quantitative analysis can be applied to a wide variety of data. Students will also gain a sense of the strengths and weaknesses of quantitative data analysis and under what circumstances the tools learned in the class are best applied in practice. The course seeks to train technically competent, intellectually critical practitioners and scholars who are able to apply quantitative methods in a wide range of settings, and who are also aware of the wider analytic context into which these approaches fit. There is a focus throughout the course on epistemology and the ethics of claim-making. Over the course, students will deepen their understanding of how claims are made, how claims are connected to different forms of evidence, and what makes different kinds of claims credible.

• Study Protocol
• Open access
• Published: 18 May 2024

Co-designing strategies to improve advance care planning among people from culturally and linguistically diverse backgrounds with cancer: iCanCarePlan study protocol

• Ashfaq Chauhan 1 ,
• Upma Chitkara 1 ,
• Ramya Walsan 1 ,
• Ursula M. Sansom-Daly 2 , 3 , 4 ,
• Elizabeth Manias 5 ,
• Davinia Seah 6 ,
• Angie Dalli 7 ,
• Nadine El-Kabbout 8 ,
• Thit Tieu 9 , 10 ,
• Mashreka Sarwar 10 ,
• Misbah Faiz 11 ,
• Nancy Huang 12 ,
• Vitor Moraes Rocha 13 ,
• Abhijit Pal 14 &
• Reema Harrison 1  

BMC Palliative Care volume  23 , Article number:  123 ( 2024 ) Cite this article

Metrics details

Advance care planning (ACP) describes the process of supporting individuals at any age or stage of health to consider and share their personal values, life goals, and preferences regarding future health care. Engaging in ACP is associated with better-quality of care in which people receive care in lines with their wishes, values and preferences. Direct translations of ACP guides and resources do not attend to the considerable inter- and intra-ethnic variations in cultural and religious or spiritual beliefs that shape preferences among people from culturally and linguistically diverse (CALD) backgrounds. ICanCarePlan is a three-year project that aims to determine the prevalence of ACP documentation among people from CALD backgrounds with cancer, identify resources available and their use to support ACP among CALD communities, identify barriers and facilitators of person-centred ACP, and to develop, through co-design with consumers and clinicians, approaches that enhance the process ACP for people from CALD backgrounds.

A mixed-method sequential approach will be used comprising of four studies. Study one is retrospective medical record review of approximately 1500 medical records to establish the prevalence of ACP documentation among CALD patient records in cancer services. Study two is a document analysis synthesising the resources available in the Australian health system to support ACP. Study three is a qualitative study with healthcare staff and consumers to explore barriers and enablers of person-centred ACP. Evidence generated from studies one to three will inform the conduct of co-design with stakeholders to develop approaches to improve ACP processes among CALD communities. Language, technical and financial support for meaningful involvement with consumers from CALD backgrounds throughout this project is outlined. A plan for distress management is also made due to sensitive nature of the topic. The research project has also established a project steering group consisting of three consumer members who are from CALD backgrounds.

The project will address a national priority issue for a growing population of CALD communities in Australia. The project will provide novel evidence of ACP among CALD communities and novel strategies developed with stakeholders to enhance uptake and experiences of ACP.

Peer Review reports

Introduction

Advance care planning (ACP) describes the process of supporting individuals at any age or stage of health to consider and share their personal values, life goals, and preferences regarding future health care [ 1 , 2 , 3 ]. ACP is a part of person-centred care; ACP should occur across the continuum of care, integrating specific values, goals and preferences with shared decision-making as care evolves [ 1 , 2 ]. For people with life-limiting disease, ACP provides individuals with opportunities to extend their autonomy in decision making to stages of life in which they are unable to make decisions for themselves [ 4 ]. ACP aids families and health care providers to make informed choices and to develop care plans aligning with patients’ values, goals and personal preferences [ 5 ]. In enhancing person-centred care and decision-making, ACP is associated with reduced hospitalisation, intensive care unit admission, invasive medical procedures at the end of life, and reduced stress, anxiety and depression amongst patients and support persons [ 5 , 6 , 7 , 8 , 9 , 10 ]. As a result, ACP is ultimately associated with improved quality of life for patients and carers [ 4 ].

Culturally and linguistically diverse (CALD) is a term used in Australian context to describe people who are born overseas or have a parent born overseas, or who speak a language other than English at home or engage in a cultural or religious practices that are different to the mainstream practices [ 11 , 12 ]. A narrative review of 43 studies published between 2017 and 2022 identified that culture, ethnicity and language proficiency influence opportunities for ACP, exposing CALD communities to potentially burdensome health care at the end of their life [ 13 ]. The review also identified that rate of uptake of ACP and the patient’s desire to talk and plan about death was related to length of stay in the destination country, acculturation and cultural and religious beliefs of ACP akin to defeat and competing with God [ 13 ]. Effective communication between healthcare staff and consumers (patients and their family or care support person) is an essential element of the ACP process [ 14 , 15 ]. Limited proficiency in English language was identified as a key factor contributing to poor quality ACP; a systematic review of 10 studies examining the use of interpreters among people with cancer with low-English proficiency identified inadequate goals of care discussions when professional interpreters were not used [ 16 ].

ACP can take many forms; when formally documented, an Advance Care Directive (ACD) is a formal plan of a person’s wishes and preferences about their future care. ACP often occurs informally and includes any instance of information sharing between healthcare staff, patients and/or their support person about their wishes, values and preferences for care [ 5 , 6 , 17 ]. There is limited evidence of the uptake of any form of ACP among people from CALD backgrounds experiencing cancer; limited administrative socio-cultural data available in patient records is a key challenge for generating this evidence. One large prospective audit study of 4,187 records of adults aged 65 years and over showed that there was a lower prevalence of completed advance care directives among those born outside of Australia (21.9%) compared to those born in Australia (28.9%) [ 17 ]. Further, the extent to which socio-cultural variables such as language spoken at home, preferred language, interpreter use, country of birth or parent’s country of birth, religion and time spent in the country of residence collectively influence the uptake of ACP is unclear.

Intra- and inter-group differences in the preferences, customs, values and expectations of care towards the end of life are notable among diverse CALD populations, reinforcing the importance of ACP for CALD communities. Documented differences include sharing the burden of worry and/or caregiving, attitudes towards explicit talk about death and dying within clinical encounters, traditional approaches as part of supportive care, and desire to be cared for/to die at home [ 7 , 8 ]. Yet healthcare staff and consumers have limited access to support them in engaging in ACP. Direct translations of ACP guides and resources do not attend to the range of cultural, religious or spiritual beliefs that shape preferences for end-of-life care (care delivered to the patient at the end of their life) for people from CALD backgrounds [ 18 , 19 , 20 ]. . Such guides may require cultural adaptation in their content and/or implementation – beyond direct language translation – to address the cultural and ethnic factors that shape preferences regarding end-of-life care and to support healthcare staff to engage in such communications. Without culturally and linguistically appropriate resources, people from CALD backgrounds may be left without the required support to engage in ACP and may be exposed to poor quality of care at the end of their life that is not aligned with their preferences, values or needs [ 21 , 22 ].

The iCanCarePlan project aims to address this gap by supporting ACP among people with cancer from CALD backgrounds. The project aims to provide novel evidence of the uptake and experience of ACP among CALD communities, resources available to support staff and consumers, and to co-design evidence-based approaches to improve the process of ACP between healthcare staff and CALD populations .

To determine the uptake and nature of ACP amongst people from CALD backgrounds experiencing cancer and examine socio-cultural factors predicting the uptake.

To characterise the resources available to support ACP in the Australian health system context and determine the extent of their relevance for people from CALD backgrounds.

To explore barriers and facilitators to ACP amongst people from CALD backgrounds with cancer and their clinicians.

To co-design a new or adapted culturally appropriate strategy to support person-centred, high-quality ACP for people from CALD backgrounds experiencing cancer.

Methods and analysis

Study design.

A mixed method sequential approach will be used comprising four studies (Fig.  1 ). A mixed-method approach [ 23 , 24 ] was selected to integrate information about the evidence of the extent of ACP (uptake and nature of ACP) among CALD populations, then identify resources available to support healthcare staff and consumers and the factors (barriers and facilitators) that have impact on ACP with CALD communities. This knowledge will inform a co-design process as the final study of the project. Co-design workshops will be conducted with consumer, policy and clinician stakeholders to collectively identify the target issue(s), design a solution(s) and develop a plan that will be used by the project team to implement the proposed solution(s).

Pictorial representation of iCanCarePlan project comprising of four studies

Study 1: retrospective medical record review

Retrospective medical record review will be used to address objective one as an established approach to data collection pertaining to ACP. This approach has been used in past studies to determine the prevalence of ACP documentation [ 5 , 17 ]. This study methods will be guided by our prior medical record review research in Australian cancer services [ 25 ].

Study 1 will be conducted across three health services providing comprehensive cancer and/or palliative care to patients from CALD backgrounds with cancer. These services provide care in inpatient, outpatient and in the community setting. The services are located in three distinct government administrative areas in the state of New South Wales that have large population of people from diverse CALD backgrounds [ 26 ]. These three health services have been purposefully selected as they attend to a diverse demographic of CALD communities [ 26 ].

A total of 1500 medical records will be reviewed (500 at each site). This sample size is sufficient to address the study objectives. To determine the prevalence of ACP documentation based on estimated rate of 25% of ACP completion and 5% margin of error, a minimum sample size required is 300 records [ 27 ]. We will also explore association between prevalence of any ACP documentation with the seven socio-cultural variables that are recommended by the Australian Bureau of Statistics in their Standards for Statistics on Cultural and Language Diversity [ 28 ]. These seven variables are country of birth, language spoken at home, preferred language, interpreter required, year of arrival in Australia, religious affiliation and if one/both parents born overseas. Based on the formula n  = 100 + 50(i) where (i) is the number of independent variables, minimal sample size required to examine the association is 450 medical records [ 29 ]. The sample size of 1500 is sufficient to explore the association between the presence of any ACP documentation and the seven socio-cultural variables outlined [ 29 ].

Eligibility and recruitment

A medical record will be eligible for inclusion if: (a) it belonged to a person from CALD background (born outside of Australia or had any/both parents born outside of Australia, speaks a language other than English at home or requires an interpreter) AND (b) there is a diagnosis of cancer that has poor prognosis, AND (c) it belongs to a person with cancer who had their first episode of care between January 2017 – December 2020 (an ‘episode of care’ defined as being seen by a health professional at the participating health service for a cancer-related illness and/or management for the first time). No age restrictions will be in place. Inclusion of cancers with poor prognosis for adults (> 18 years of age) and children and young adults (< 18 years of age) is based on identification by Cancer Australia National Cancer Control Indicators (Supplementary File A ) [ 30 , 31 ]. Records that do not meet the eligibility criteria will be excluded.

Data extraction

Each service will generate a list of patient records and the research team will apply the inclusion criteria to select eligible records using a random number generator. Once the eligible patient records are identified, a data extraction template (Supplementary File B ) will be used to collect data. Each medical record will be retrospectively reviewed from the time of their first episode of care to the current date or until the date for when the data is available.

Data analysis

Data analysis will be carried out using the R statistical software package. The primary outcome of interest will be the prevalence and type of ACP documentation (such as presence of an Advance Care Directive, resuscitation plan, conversation about goals of care or place of death) in the paper and/or electronic based medical records of patients with cancer from CALD backgrounds. Descriptive statistics (e.g., frequency, percent, sum, mean, median, standard deviation) will be used to describe the sample characteristics and frequency and nature of ACP documentation. Chi-square tests of independence will be used to compare key variables (such as age, sex, country of birth, language spoken at home, interpreter required, preferred language etc.) and logistic regression will be used to identify the association between the presence of ACP documentation to socio-cultural variables of the diverse CALD populations.

Study 2: document analysis

Altheide’s document analysis approach will be used to address objective two, to characterise and explore the relevance of current resources available to healthcare staff and consumers from CALD backgrounds that support them during the process of ACP [ 15 , 32 , 33 ].

The study will examine resources available at all levels of the Australian healthcare system. The websites of Australian government departments and health agencies at national, state and local health administrative levels will be searched. Relevant non-government organisations that have key focus on ACP, palliative and end-of-life care will be searched to identify and include eligible resources for analysis.

Eligibility and inclusion

Eligible data sources will comprise of contemporary resources (available in print, audio or video format) published from January 2013 to June 2023. Resources that provide guidance for the communication process for ACP (for example: question guides, how to guides, fact sheets, toolkits, techniques for communication other similar documents) will be eligible for inclusion. Strategic plans, policy documents, frameworks and implementation plans will be excluded as they do not provide the information relevant to the study objective. Resources relating to education modules and professional development courses will also be excluded.

The data extraction will be completed in accordance with the iterative process of search, selection and extraction outlined in prior research using the Altheide’s approach [ 15 ]. Two researchers will complete an initial search of the eligible organisations (Supplementary File C ) websites using key words (palliative care, end-of-life care, life support care, advance care directive, advance care planning, advanced personal plan, life wishes, substitute decision-maker, carer decision maker) to identify initial set of resources. These key words have been developed using collective knowledge and experience of the research team and relevant literature [ 34 , 35 ]. These resources will then be subjected to inclusion criteria by the two same researchers who completed the initial search and eligible resources will be identified. Any discrepancies during this stage will be resolved through discussion with the project lead. Data extraction tool will be developed and used to collect consistent information from the eligible documents relevant to study objective. The two researchers will complete the data extraction using the data extraction tool for the subset of the resources. The findings will be compared and discussed in a meeting with the project lead. Following this, one researcher will complete the data extraction of the remaining eligible resources with findings discussed in regular meetings with the project lead.

Narrative synthesis will be employed for evidence synthesis [ 15 ]. Contents of the eligible resources that provide guidance or support to consumers from CALD backgrounds or healthcare staff for the ACP will form the unit of analysis. The data extracted will be analysed to present the characteristics of the resources. Frequency, count and proportion of the resources will be presented under the categories of total number of resources, form (print, audio, video), source (government or non-government), target group (healthcare staff and/or consumers) and type of settings (such as primary, secondary, community, specialist or other). This will be followed by presenting a narrative description of operationalisation of ACP process with consumers from CALD backgrounds. We will examine the extent of cultural, religious or spiritual, language and other specific considerations for ACP with diverse CALD communities outlined or discussed in the included resources. We will also examine consumer involvement in development of the resources.

Study 3: qualitative data collection with healthcare staff and consumers

Qualitative data in the form of focus groups or interviews with healthcare staff and consumers will be used to address the objective three. Focus groups and semi-structured interviews provide a flexible approach to data collection to obtain in- depth data on experiences and expectations of ACP [ 36 , 37 ]. Given the nature of the discussion, some participants (especially consumers from CALD backgrounds) may not wish to participate in the focus groups. These participants will be provided the opportunity to participate via one-on-one semi-structured interviews with the researcher.

Evidence of the current barriers and enablers to ACP and use of current resources with CALD communities experiencing cancer will be captured nationally through focus groups with healthcare staff and consumers from CALD backgrounds accessing cancer care.

Number of the focus groups will be determined by emerging findings and point of saturation [ 36 , 38 ]. Approximately four to six focus groups (two-three focus groups with healthcare staff and two-three with CALD consumers and consumer representatives), with a total of up to 48 participants will be conducted. Each focus group will consist of six to eight participants. This sample size is sufficient to allow in-depth discussion on the topic while managing the amount of information collected to analyse the data [ 36 ].

Recruitment and eligibility

Healthcare staff working in cancer or palliative care for a minimum of six months, consumer representatives from consumer organisations that cater to cancer and palliative care, and consumers from CALD backgrounds who have used cancer or palliative care services will be eligible to participate in this study. All eligible participants will be 18 years of age or older and willing to provide consent for participation.

Participant recruitment and data collection will be an iterative process with focus groups and/or interviews conducted concurrently. Purposive sampling will be used to recruit participants through multiple channels (social media, networks and consumer organisations). Recruitment will be based on participant opt-in; contact details of the research team will be distributed through study advertisements (poster, social media posts) and potential participants will be provided with opportunity to contact research team first. Eligibility screen will be conducted, and eligible participants will be provided with study information sheet and consent form (PICF) prior to data collection. For participants who require language support during screening and recruitment, bilingual fieldworkers or interpreters will be used to convey the information and obtain consent as required. PICFs will be made available to participants in their preferred non-English language as needed.

Based on our previous work [ 39 ], we have established a project steering group that consists of three consumer members from CALD backgrounds with lived experience of cancer. Feedback from these three consumer members was sought for developing consumer facing research material such as the participation information sheet and recruitment advertisement to facilitate participation of consumers from CALD backgrounds in interviews or focus-groups and subsequent co-design workshops. These consumer members will also support the research team in developing a recruitment strategy for recruiting people from CALD backgrounds in this research.

Data collection

Data collection will commence after the consent is obtained and recorded. An interview guide informed by thematic domains framework (TDF) will be used to guide the qualitative data collection [ 40 , 41 ]. The TDF is selected to elicit responses from the participants to identify factors (barriers and facilitators) responsible for delivery of quality ACP with people from CALD backgrounds with cancer [ 42 ]. The focus groups/interviews will be conducted either online, face-to-face or using a hybrid model (combination of face-to-face and online participation) as suitable to the participants.

Data will be analysed using the Framework method [ 43 ]. TDF will be used as the framework for this analysis. Study data will be managed using NVivo [ 41 ]. The audio recording of the focus groups/interviews will be transcribed verbatim. Data will be transferred to NVivo, and analysis will be conducted in it. Data analysis will draw out common experiences and perceptions regarding the barriers and facilitators to ACP amongst people from CALD backgrounds experiencing cancer against the TDF framework. Data will be both inductively and deductively analysed. The data will be analysed and coded under the categories of TDF. A working analytical framework will be developed in the initial stage through an iterative process of re-reading and coding the transcripts between two researchers and the project lead. A Framework Matrix charting the final categories and codes will be developed. Following this, themes will be developed with preliminary themes refined in consultation with contribution from the wider research team.

Study 4 – co-design approaches to improve quality ACP

Adapted experienced-based co-design (EBCD) approach will be used to conduct this study. This approach has been used in our prior work to co-design health service interventions with relevant stakeholders including consumers from CALD backgrounds [ 39 , 44 ]. Adapted EBCD consist of two adaptations made to the co-design approach. These two adaptations are (a) inclusion of a preparatory stage to identify and meet various support needs of the co-design members and (b) inclusion of a consumer co-facilitator to mitigate power imbalance during co-design workshops [ 39 , 44 ]. These two adaptations aim to improve the meaningful participation of co-design members and improve their experiences of co-design process [ 39 ]. Following the preparatory phase, a series of three co-design workshops will be conducted accompanied by an introductory meeting between all co-design members and a set of preparatory meetings in between co-facilitators prior to each workshop (Fig.  2 .).

Co-design process

Preparatory work prior to co-design

Preparatory work will be undertaken to support meaningful participation of consumers from CALD backgrounds in co-design workshops [ 39 , 45 ]. This involves identifying and meeting the support needs of the co-design members and ensuring equal power distribution between all members during co-design.

Identifying support requirements

Based on our prior work [ 39 , 44 , 45 ], language, technological and financial support needs of the co-design members will be identified and addressed to enhance equal participation of all co-design members in the co-design workshops [ 45 ]. Professional interpreters or bilingual research fieldworkers will be used to provide language support as required by potential participants. Through our existing consumer co-facilitator network [ 46 ], we have access to bilingual research fieldworkers who can speak 11 languages. The members of this network are trained in conducting research and have knowledge of the research project. In a case where the language support is not provided with bilingual research fieldworker, an interpreter will be used. The mode of meeting (online, face to face or hybrid) will be determined based on the preferences of co-design members. Technical support will be provided via one-to-one communication with participants to facilitate online participation in the co-design workshops where necessary. Consumers and their representatives will be remunerated for their time to take part in the project appropriate to the nature of their roles based on the rates proposed by Health Consumers New South Wales [ 47 , 48 ].

Strategies to mitigate power imbalance during co-design

To enhance meaningful participation of consumers from CALD backgrounds and to minimise the power imbalance between researchers and consumers in co-design workshops, consumer co-facilitators will assist the research co-facilitator to conduct the co-design workshops [ 49 ]. Employing consumer and research co-facilitators in co-design encourages a more inclusive culture to encourage engagement and provide co-facilitators to adequately identify and address any issues and shifts in power dynamics [ 49 ]. Consumer co-facilitators will be provided a role description and receive training in the research topic and co-facilitation prior to the co-design workshops.

Co-design procedure

Approximately 4–6 members (2–3 consumers/consumer representatives and two-three healthcare staff) will be involved as members of the co-design group [ 39 , 50 ]. Based on our prior work with diverse consumers, this size of group membership provides an opportunity for all members to contribute fully and effectively including with use of interpreters and support persons [ 44 ]. The co-design group will also consist of research co-facilitators, a consumer co-facilitator and a bilingual fieldworker as needed relevant to the study population [ 39 ]. Those who have taken part in the focus groups/interviews will be requested to indicate their interest if they wish to be contacted about co-design workshops. Those who indicate willingness to be contacted will provide their email and telephone contact details for this purpose and be invited to take part as co-design members until 4–6 members have been recruited. The consumer co-facilitator will be recruited to co-facilitate each group via the existing consumer co-facilitator network. If any member withdraws from the co-design group, a new member will be invited to join the process. Recordings of the initial session(s) will be shared with the new members if they are joining late in the process. The change in co-design group members in between workshops would not impact the validity of the process but may introduce broader range of perspective enhancing the process. Written consent will be obtained prior to the conduct of co-design workshops.

Co-design workshops

The codesign groups will be convened to adapt, design and implement solutions to the priority issues identified through studies one to three. Written informed consent will be obtained prior to the conduct of co-design workshops. A suitable place to conduct the workshops will be identified in consultation with the co-design members. The co-design group will meet for no more than 10 h in total; approximately for 2.5 h for three times over a period of six weeks. The duration and timing of the groups will be determined by the members to ensure suitability. A separate introductory meeting will be conducted between the group members for 30-minute prior to first co-design workshop. In this meeting, the group will develop terms of reference that will determine their ways of working and the preferred mode of meeting (online, face to face or hybrid) and meeting duration and frequency. Co-facilitators will meet prior to each co-design workshop to determine the scope and content of each workshop based on the progress to that point. The co-facilitators will also contact co-design members in between workshops to address any queries or concerns or to receive any feedback that members were not able to provide in the workshop. Preparatory meetings in between the workshops will allow co-facilitators to integrate theory into the content of the subsequent workshops [ 51 ].

Ensuring study quality

The programme of work has been through independent peer review process as part of the Cancer Institute New South Wales Career Development Fellowship grant awarded to project lead (RH). This programme of work is funded based on the scientific quality of the proposal. The funding also requires an annual progress report to the funder. To further ensure the study quality, a project reference group has been established that meets twice in a year. The reference group consist of three consumer members with lived experience of cancer along with members from relevant policy, research, consumer interest and cancer and palliative care relevant organisations. Terms of reference have been co-developed with member of the project reference group. The main function of the reference group is to provide oversight on the project processes and progress against the research objectives.

The research project has received ethics approval from two National Health and Medical Research Council (NHMRC) accredited Human Research Ethics Committees (Reference number: 2023/ETH00216 and 520,231,235,452,528) by South-Western Sydney Local Health District Human Research Ethics Committee and Macquarie University Human Research Ethics Committee. Through the ethics applications and approvals, various ethical considerations have been explored and a risk mitigation plan created for each matter employing three main strategies.

Firstly, recognising the complexity of the programme of work involved, a research team consisting of project lead, project manager and associate investigators has been established. The research team will provide accountability for the conduct of the research activities. Secondly, recognising involvement of consumers from diverse language and cultural backgrounds and risk associated with potential for ineffective communication, budget has been allocated for translating consumer facing material and employing bilingual fieldworkers or interpreters in the research activities.

Thirdly, recognising the sensitivity of the topic area, the discussion about ACP may bring about distress to potential participants during qualitative data collection and in co-design workshops. This issue may arise in group discussions or during one-on-one interviews [ 52 ]. A process will be implemented whereby a list of supportive organisations will be provided to the participants prior, during and after each focus group/interview and co-design workshops. At the start of each focus group or interview and co-design workshop, research team will inform participant to let the research team know if they experience any distress. Participants will also be informed that they do not have to answer every question, that they can take a break from discussion at any time if they wish and if online, they can close their camera or video application if they need to [ 53 ]. During the discussion, if the researcher think that the participant is experiencing distress, the researcher will pause the discussion and ask if the participant requires a break. The researcher will also offer the list of support organisations if the participant wishes to speak with a relevant organisation. Participant will be asked if they require a referral for further support or if they require the researcher or the research team to contact their local general practitioner [ 53 ]. After each discussion, the researcher will follow-up with participants and co-design members to check on them. The project team also includes a practising clinical psychologist who could provide referrals for further support as needed.

Anticipated operational difficulties

The main anticipated difficulty relating to this program of work is recruitment of consumers from CALD backgrounds in qualitative data collection. Discussion about experiences and expectations of ACP may bring distress among consumers from any backgrounds, but particularly for people from CALD backgrounds where cultural meaning of disease such as cancer and death and dying is different to that of the non-CALD population [ 54 , 55 ]. Further varied cultural practices may dictate consumers readiness to talk about their experiences of ACP. Perception of a cancer as a ‘shameful’, stigmatised disease may further complicate the recruitment process [ 56 ]. To mitigate this issue, an iterative collaborative approach will be used. The researchers will identify and partner with community representatives, leaders and organisations working closely with various CALD communities to identify a recruitment strategy that would work for recruiting consumers from a particular community. This approach will be undertaken with help of the project steering group members, especially consumer members, who will assist with identification of these networks and introduce the research team where necessary. Through these connections, avenues for distributing recruitment material to recruit participants from CALD background and suitable approach for data collection (e.g. via focus group or on-one interview and most appropriate modality) will be determined. The iterative collaborative approach of working with consumer members of the project steering group and community representatives, leaders and organisations may also assist in identifying priority CALD communities to conduct language, culture or religion specific focus-groups or interviews. This approach will allow us to generate knowledge of the issues that may pertain to range of CALD populations but also be specific for some CALD communities.

Potential research, policy and practice implications

The Australian National Consensus Statement on essential elements for safe and high quality end-of-life care highlights ACP as an essential element of person-centred high quality end-of-life care [ 57 ]. Provision of culturally appropriate resources and communication have been highlighted in the Consensus Statement for achieving safe and high quality end-of-life care for people from CALD backgrounds [ 57 ]. Need for meaningful ACP conversations with priority population groups such as those from CALD backgrounds have also been identified as a national information priority by Australian Institute of Health and Welfare considering increasing population of people from diverse CALD backgrounds [ 58 ].

This program of work will contribute to advancing research, policy and practice for meaningful ACP with CALD communities in the following four ways. The medical record review study will provide a real-world data on ‘what is happening’. This study will identify gaps for communities for ACP processes and documentation. The document analysis study will help understand the current state of ‘what is available’. This study will identify gaps in the resources and where the adaptation or new strategy are required to support healthcare staff or consumers to facilitate meaningful ACP. Qualitative data collected through focus groups or interviews will inform ‘how the conversations are happening’. This study will help understand needs, desires, barriers and facilitators for meaningful ACP and will directly inform how the strategy need to be tailored to suit the needs of CALD populations. Co-design will then help partner with end service users to directly shape the strategy to improve ACP that they receive. The co-designed strategy developed will be reported in the context of quality ACP issue addressed, the adaptation made to the process, the population who co-designed the strategy and the target population for whom the co-designed strategy is relevant for. The co-design strategy will also report on potential process and outcome success measures. Application of the strategy to address diverse cultural needs will be discussed along with the need for future adaptations to suit diverse CALD populations. The plan for implementation and evaluation of the strategy will follow as next steps separate to this programme of work.

The project will address a national priority issue for a growing population of CALD communities in Australia. The project will provide novel evidence of ACP among CALD communities and novel strategies developed with stakeholders to enhance uptake and experiences of ACP. communities in Australia. The project will also provide important process related knowledge for enhancing participation of consumers from CALD communities in research concerning sensitive topics. Implementation and evaluation of the co-designed approach will be the next step.

Data availability

No datasets were generated or analysed during the current study.

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Acknowledgements

We would like to thank Sheetal Challam, Philippa Sambevski, Lisa Woodland, Lukas Hofstatter, Nadine El-Kabbout, Mashreka Sarwar, Thit Tieu, Elizabeth Manias, Angie Dalli, Ursula Sansom-Daly, Misbah Faiz and Vitor Moraes Rocha for their continuing support as members of the iCanCarePlan project steering group.

This research project is funded by Cancer Institute NSW via a Career Development Fellowship awarded to project lead Professor Reema Harrison. The Fellowship application underwent scientific peer review by the funding body as part of the funding process.

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RH conceived the project and is the project lead. AC, UC, RW and UMSD contributed to design of individual studies through regular meeting. AC and UC will be largely responsible for collecting data for the studies outlined in the project. EM, DS, AD, NEK, TT, MS, MF, NH, VR and AP provided guidance on the conduct of the studies. AC drafted the initial and subsequent draft of the manuscript with RH. UC, RW, UMSD, EM, DS, AD, NEK, TT, MS, MF, NH, VR, AP and RH provided intellectual content to the manuscript, edited and reviewed the final draft. RH acquired the funding for the project.

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Chauhan, A., Chitkara, U., Walsan, R. et al. Co-designing strategies to improve advance care planning among people from culturally and linguistically diverse backgrounds with cancer: iCanCarePlan study protocol. BMC Palliat Care 23 , 123 (2024). https://doi.org/10.1186/s12904-024-01453-z

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Selected Methods of Planning Analysis

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• Provides a detailed introduction and comprehensive description of five analytical research methods in the context of planning: i) demographic analysis, ii) economic analysis, iii) financial analysis, iv) land use analysis, and v) transportation analysis
• Demonstrates applications of the planning research methods in suitability- and impact analysis
• Illustrates the often difficult process of gathering the “right” data and understanding limitations embedded in data
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This textbook introduces fundamental methods related to planning assessment and impact analysis, which aid planners in answering the following crucial questions:

·         “Who are the people living here?” (demographic analysis);

·         “In what activities are people involved?” (economic analysis);

·         “Where in the region do these activities occur?” (land use analysis);

·         “How are people and their various human activities connected spatially?” (transportation analysis).

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Front matter, introduction: planning analysis methods.

Xinhao Wang, Rainer vom Hofe

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Dr. Wang is a Professor of Planning in the School of Planning, University of Cincinnati. He holds a Ph.D. in City and Regional Planning from the University of Pennsylvania, a Master of Community Planning from the University of Rhode Island, a Master of Science in Geo-Sciences and a Bachelor of Science in Geography from Peking University, Beijing, China. He teaches courses in Geographic Information Systems (GIS), environmental planning, statistics, and planning research methods. His research interests are in the areas of environmental planning and GIS application in planning.

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Melissa MacKay, PhD; Devon McAlpine, BSc; Heather Worte, MPH; Lauren E. Grant, PhD; Andrew Papadopoulos, PhD; Jennifer E. McWhirter, PhD

https://doi.org/10.24095/hpcdp.44.5.03

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Research article  by MacKay M et al. in the HPCDP Journal licensed under a Creative Commons Attribution 4.0 International License

Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada

Jennifer McWhirter, 50 Stone Road East, Department of Population Medicine, University of Guelph, Guelph, ON  N1G 2W1; Tel: 519-824-4120 ext. 58951; Email:  [email protected]

MacKay M, McAlpine D, Wrote H, Grant LE, Papadopoulos A, McWhirter JE. Public health communication professional development opportunities and alignment with core competencies: an environmental scan and content analysis. Health Promot Chronic Dis Prev Can. 2024;44(5):218-28. https://doi.org/10.24095/hpcdp.44.5.03

Introduction: Communication is vital for effective and precise public health practice. The limited formal educational opportunities in health communication render professional development opportunities especially important. Competencies for public health communication describe the integrated knowledge, values, skills and behaviours required for practitioner and organizational performance. Many countries consider communication a core public health competency and use communication competencies in workforce planning and development.

Methods: We conducted an environmental scan and content analysis to determine the availability of public health communication professional development opportunities in Canada and the extent to which they support communication-related core competencies. Three relevant competency frameworks were used to assess the degree to which professional development offerings supported communication competency development.

Results: Overall, 45 professional development offerings were included: 16 “formalized offerings” (training opportunities such as courses, webinars, certificate programs) and 29 “materials and tools” (resources such as toolkits, guidebooks). The formalized offerings addressed 25% to 100% of the communication competencies, and the materials and tools addressed 67% to 100%. Addressing misinformation and disinformation, using current technology and communicating with diverse populations are areas in need of improved professional development.

Conclusion: There is a significant gap in public health communication formalized offerings in Canada and many of the materials and tools are outdated. Public health communication professional development offerings lack coordination and do not provide comprehensive coverage across the communication competencies, limiting their utility to strengthen the public health workforce. More, and more comprehensive, professional development offerings are needed.

Keywords : health communication, core competencies’ professional development, workforce planning

• There have been widespread calls to transform the public health workforce in Canada.
• We conducted an environmental scan and content analysis to determine current professional development opportunities in public health communication and investigate how well they support communication-related core competencies.
• We found 45 professional development offerings relevant to public health communication in Canada, with varying coverage of the core competencies.
• Addressing misinformation and disinformation, the use of current technology and communicating with diverse populations are areas in need of improved professional development.
• This snapshot of the current state of public health communication professional development shows that coverage across the competencies is neither coordinated nor comprehensive.

Introduction

With the field of public health constantly evolving due to new knowledge from research and practice and changing technology, effective communication is critical, especially during crises. Footnote 1 Effective communication is also central to the design and implementation of public health initiatives, which impact adoption of recommended health behaviours, especially among those in underserved population groups. Footnote 2

There have been widespread calls to improve the Canadian public health system, including updating core competencies for public health and related professional development opportunities Footnote 1 Footnote 3 Footnote 4 Footnote 5 as well as public health communication. Footnote 6 Footnote 7 Changes in the information ecosystem have altered methods of communication and increased the threat of misinformation, undermining trust in public health communication. Footnote 8 Footnote 9 This is especially apparent in the context of social media, which is an important tool for delivering public health messages. Footnote 1 Footnote 9

Without the opportunities to continually update and adapt their communication competencies and skills, public health practitioners risk losing their credibility and the public’s trust, negatively affecting the health of Canadians. Footnote 1 Professional development allows for the enhancement of existing skills and behaviours and acquisition of new knowledge and attitudes in order to meet workforce demands.

In 2008, the Public Health Agency of Canada ( PHAC ) published Core Competencies for Public Health: Release 1.0 (“ PHAC core competencies”) after extensive consultation with public health researchers and practitioners across the country. Footnote 10 The 36 PHAC core competencies are organized into seven categories, one of which is communication. Footnote 10 At the time of writing, the PHAC core competencies were undergoing renewal and modernization. Because of the age of the current PHAC core competencies, other public health competency frameworks may help inform Canadian public health workforce planning.

Health Promotion Canada has a framework for discipline-specific competencies for health promotion (“ HPC competencies”) based on the PHAC core competencies. Footnote 11 The Council on Linkages Between Academia and Public Health Practice (“Council on Linkages”) in the USA has foundational core competencies for public health practitioners; Footnote 12 these core competencies have been regularly revised since their release in 2001 and provide an up-to-date framework that reflects modern communication requirements, including addressing the infodemic and culturally appropriate communication. Footnote 12

There are similarities across the three competency frameworks, including tailoring communication to various audiences, choosing the right communication channel(s), mobilizing communities and using technology effectively. The extent to which communication competencies from these frameworks inform professional development opportunities for public health communication is unknown.

Gaps have been identified in the public health communication courses offered by the master of public health programs in Canada. Footnote 13 Footnote 14 Also, research into online continuing education programs found that only about half the courses offered in 2015 included communication as a topic. Footnote 15 Although several online courses are available for public health professionals in Canada, Jung et al. Footnote 15 found that these did not provide comprehensive coverage of the PHAC core competencies, including within the communication domain; nor were they readily accessible through a central online database.

Given the significance of communication in public health practice and its focus in public health competency frameworks, it is important to understand the opportunities and resources currently available and how these align with the relevant competency frameworks. Identifying current professional development offerings for public health practitioners will also highlight the opportunities for building workforce competence and communication capacity.

This current research aims to determine the availability of public health communication professional development opportunities and the extent to which they support core competencies in communication. The objectives of this research include:

• using an environmental scan to identify currently available Canadian professional development opportunities relevant to public health communication; and
• conducting a content analysis to describe how these identified professional development opportunities align with communication competencies from the relevant frameworks ( PHAC core competencies, HPC competencies, and Council on Linkages competencies).

We conducted an environmental scan to determine the current professional development landscape that supports public health communication competencies in the Canadian workforce. Our search methods were guided by previous research on competencies for public health and continuing education. Footnote 16 Footnote 17 Following the steps outlined by Bengtsson Footnote 18 and Krippendorff, Footnote 19 we analysed the content of all the professional development opportunities identified in the scan to determine their nature and the degree to which they support the development of public health communication competency.

Search strategy

First, the research team searched, by way of a Google site search (site: URL search terms) using the term “health communication,” the entire contents of websites of public health organizations known to them.

Next, we conducted an Internet search using the Google search engine and the following search terms: “health communication,” “public health,” ”continuing education,” “Canada.” A subsequent search used the search terms “health communication,” “public health,” “course,” “Canada.” Consistent with methodological examples and recommendations, we reviewed the first 10 pages of results of each search. Footnote 17 Footnote 20 The same two searches were also run using the Ontario Public Health Libraries Association custom Google search engine, Footnote 21 the grey literature database CABI Global Health Footnote 22 and the custom Google search engine developed by Queen’s University Library. Footnote 23 Other resources known to the research team were also included.

Search criteria

Two researchers ( MM and JEM ) independently reviewed the professional development offerings for relevance to the following inclusion and exclusion criteria and resolved all conflicts by discussion. For a professional development opportunity to be included, it had:

• to be offered or be available within the last 12 months (materials and tools may still be available online long after their initial publication);
• to be widely available and applicable to Canadian public health practitioners;
• to reoccur as a multistep program offered to different public health organizations and/or allow repeated access through online platforms;
• to be in English;
• to be offered in Canada or be available to Canadians;
• to be relevant to Canadian public health infrastructure and governance; and
• to be related to public health communication.

Included were “formalized offerings,” that is, training opportunities such as certificate programs, courses, graduate programs, summer institutes, webinars and online learning programs, and “materials and tools,” that is, resources such as guidebooks, white papers, expert panel reports, toolkits, guidelines and briefing notes, conference proceedings, blog posts, factsheets, toolkits and websites.

Offerings were excluded if they were single occurrence webinars, conferences or workshops; and/or limited in geographical relevance or offered in a relatively small geographical area or organization (e.g. one local public health unit).

Data collection

One researcher ( HW ) collected the data between 13 November 2022 and 6 December 2022 and recorded the information on an Excel spreadsheet. Footnote 24 The following information was collected for each formalized offering: name, description, type (e.g. certificate program, webinar), format (e.g. hybrid, online), intended audience, time commitment, cost, the institution providing the offering, the country providing the offering and its geographical reach, date last offered, currently offered (Y/N), the URL , the search date and the search source. The following information was collected for materials and tools: title, author, description, type (e.g. guidebook, toolkit), intended audience, location, date, the URL , the search date and the search source.

Content analysis

The communication-related competencies from the PHAC core competencies, Footnote 10 the HPC competencies Footnote 11 and the Council on Linkages Footnote 12 were used to assess the degree to which the professional development offerings support public health communication competencies ( Table 1 ).

Three researchers ( MM , HW and JEM ) created a codebook describing key variables identified during data collection and the communication-related competencies from the frameworks described above. (This codebook is available online .) Subvariables for each competency that reflected the named audiences, channels, tools and techniques were also captured. Professional development opportunities could be coded for the overall competency and may or may not be coded for the various subvariables depending on whether the specific audiences, channels, tools and techniques were covered. The codebook was validated prior to coding. Two researchers ( HW and MM ), working independently, coded the full dataset, discussing and resolving all conflicts along the way.

Statistical analysis

Descriptive statistics (frequencies) were calculated using Excel Footnote 24 to assess how each of the professional development opportunities support the communication competencies. We used RAWGraphs Footnote 25 to present the data visually.

The environmental scan uncovered a total of 45 professional development opportunities related to public health communication. Of these, 16 (36%) were formalized offerings and 29 (64%) were materials and tools. Three of the 16 formalized offerings were available and analyzed in full. The remaining 13 were analyzed based on the summary information available (most often because they were behind a paywall). All materials and tools were available and analyzed in full.

Details on the formalized offerings and materials and tools are available online .

Characteristics of professional development opportunities

Just over half of the 16 formalized offerings (n = 9; 56%) and most of the 29 materials and tools (n = 26; 90%) originated from Canada ( Table 2 ). While all the formalized offerings were offered in the last 12 months (and thus met our inclusion criteria), only one (3%) set of materials and tools was published in the last 12 months and only six (21%) in the last 5 years, although all were available online within the last 12 months, thus meeting our inclusion criteria.

Just over two-thirds of the formalized offerings (n = 11; 69%) and all the materials and tools (n = 29; 100%) were offered online asynchronously; 13 of the formalized offerings (81%) and 28 of the materials and tools (97%) focused on general public health practitioners. The most common formalized offerings were courses (n = 6; 38%); were focused on knowledge mobilization (n = 5; 31%); and were offered by academic institutions (n = 4; 14%). The most common materials and tools were resources (n = 12; 41%); were focused on general health communication (n = 10; 34%); and were offered by arms-length organizations (n = 8; 28%).

Professional development opportunities were delivered by various organizations and institutions. Formalized offerings were mostly offered by academia (n = 6; 38%), government-funded arms-length institutions (n = 3; 19%) and hospitals (n = 3; 19%). Materials and tools were mostly offered by government-funded arms-length institutions (n = 8; 28%), provincial governments (n = 8; 28%) and academia (n = 4; 14%) ( Table 1 ; Figure 1 ). No formalized offerings were provided by public health units, NGOs or provincial governments, and very few materials and tools were offered by public health units and professional associations (n = 1 each; 3%) ( Table 1 ; Figure 1 ).

Abbreviations: Council on Linkages, Council on Linkages Between Academia and Public Health Practice; HPC , Health Promotion Canada; PHAC , Public Health Agency of Canada. Notes: The legend provides two reference points (smallest circle = 4 offerings and largest circle = 29 offerings) visualized in the figure. Formalized offerings: certificate (programs), courses, graduate programs, summer institutes, webinars. Materials and tools: conference proceedings, blog posts, briefing notes, expert panel reports, factsheets, guidebooks, toolkits, websites, guidelines.

Competencies within professional development opportunities

Overall, across the professional development opportunities (formalized offerings and materials and tools combined; see Table 1 ), competencies related to tailoring information (n = 44; 98%), using different communication strategies (n = 43; 96%) and communicating with internal and external audiences (n = 42; 93%) were the most supported; competencies related to misinformation and disinformation (n = 12; 27%), current technology (n = 25; 56%) and using media (n = 33; 73%) were the least supported (data not shown). Figure 2 shows the alignment of the professional development offerings with the competency frameworks broken down by formalized offerings (n = 16) and materials and tools (n = 29).

Note: The legend provides two reference points (smallest circle = 1 offering and largest circle = 5 offerings) visualized in the figure.

Alignment with PHAC communication competencies

On average, formalized offerings covered 2.25 (range: 0–4) out of the 4 communication-related PHAC core competencies and materials and tools covered 3.55 out of these 4 competencies (range: 2–4) per professional development offering. The PHAC core competency most commonly supported by professional development opportunities was interpreting information, which was addressed by all 29 of the materials and tools and three-quarters (n = 12; 75%) of formalized offerings ( Table 3 ). Communication skills was similarly supported by all of the materials and tools and almost two-thirds (n = 10; 63%) of formalized offerings. Mobilizing people was slightly less supported with 90% (n = 26) of materials and tools and 50% (n = 8) of formalized offerings addressing it. The least supported competency was current technology with 66% (n = 19) of materials and tools and 38% (n = 6) of formalized offerings addressing it.

The types of intended audiences were less frequently addressed by formalized offerings compared to materials and tools ( Table 3 ), with colleagues the least addressed audience type. Professional development opportunities most often addressed interpreting information for communities, while professional audiences were least covered. Further, social marketing techniques for mobilizing individuals and communities were not well addressed by the professional development opportunities. Finally, formalized offerings infrequently covered specific technologies identified in the competencies, while materials and tools addressed using websites and social media in approximately half of the resources that addressed this competency.

Alignment with HPC communication competencies

Overall, materials and tools were strongly aligned with all the HPC communication competencies ( Table 4 ). Tailoring information to specific audiences was the most widely addressed competency by both formalized offerings and materials and tools. Coverage of the different communication methods varied, with the media (traditional and new media) addressed by seven (44%) formalized offerings and 19 (66%) materials and tools, and information technologies addressed by just two (13%) formalized offerings and 10 (34%) materials and tools. While communicating with diverse populations was well supported by formalized offerings (n = 7; 44%) and materials and tools (n = 27; 93%), it was often addressed exclusively in the context of health literacy (n = 2/7 [29%] formalized offerings; n = 15/27 [52%] of materials and tools).

Alignment with Council on Linkages communication competencies

Overall, the materials and tools had more comprehensive alignment with the Council on Linkages communication competencies based on the information available, except for addressing misinformation and disinformation ( Table 5 ). This competency subvariable had the lowest support from professional development opportunities with only four (25%) of formalized offerings and eight (28%) of materials and tools addressing misinformation and disinformation.

Although the remaining three competencies (communication strategies, internal/external audiences, facilitate communication) were broadly addressed by many professional development opportunities, there was less focus on some key elements. Specifically, while 17 (59%) of materials and tools addressed communicating with internal audiences, only two (13%) formalized offerings addressed this element of the competency.

This study examined the professional development opportunities for public health communication widely available currently or within the last 12 months, in English, to Canadians or relevant to Canadian public health, and how closely aligned they are with public health communication competencies relevant in Canada ( PHAC and HPC ) and the USA (Council on Linkages).

We found 45 offerings related to public health communication of which 16 were formalized offerings (training opportunities, e.g. certificate programs, courses, webinars) and 29 were materials and tools (resources, e.g. guidebooks, toolkits, reports). Less than one-quarter of the materials and tools were published in the last 5 years. The older age of some materials and tools may have contributed to the competency gaps in current technology and in addressing misinformation and disinformation. Most often, formalized offerings focussed on knowledge mobilization while materials and tools focussed on general health communication.

Professional development offerings were not developed or coordinated by a governing body, but were offered by different organizations and agencies across Canada and the USA . Overall, the formalized offerings address fewer competencies relative to the materials and tools; however, this may be, at least in part, because we were only able to analyze summary materials for the majority of formalized offerings whereas all materials and tools were available and analyzed in full.

Competencies are the integrated knowledge, skills, attitudes/values and behaviours that public health practitioners and organizations must possess for effective public health practice. Footnote 26 Public health organizations can take competencies into account when recruiting personnel, assessing job performances and identifying professional development needs. Footnote 26 Workforce training and continuing education are an essential part of competency development, especially when there is a lack of graduate training options in communication and other competencies, as was found in Canada. Footnote 14 Footnote 15 The Canadian Public Health Association has recommended workforce training in modernized competencies as key for strengthening the public health system. Footnote 1 Footnote 27 PHAC used to offer Skills Online, an eight-module professional development program that directly supported the core competency categories. Footnote 28 The results of this study show that the professional development opportunities currently available do not cover all the PHAC core competencies, with formalized offerings averaging 2.25 competencies per opportunity and materials and tools averaging 3.55 competencies per opportunity. No equivalent comprehensive training program fills this gap.

Our research was specific to the public health communication categories; in fact, we found that there is no comprehensive professional development program for public health communication. What is available is a range of programs offered by many different types of organizations and agencies, some of which may not be up-to-date and which do not comprehensively support current communication competency development needs. While a comprehensive federal training program such as Skills Online Footnote 28 may provide coordinated training across the full range of core competencies (including communication), the smaller professional development offerings could not be expected to be equally comprehensive. Rather, the professional development offerings provided by the various organizations and institutions were more targeted and not designed to cover the full range of communication competencies. Examining the professional development opportunities collectively allows for understanding what is available, how the opportunities support the development of communication competencies, and what areas of opportunity exist for public health communication in the absence of a comprehensive competency-based federal training program.

Compared to the formalized offerings, the materials and tools were more aligned with the communication-related core competencies; however, practitioners need to seek out these resources, without the benefit of a facilitated structure such as could be expected from a course. Diverse effective training includes online courses, mentorship, just-in-time training and community-engaged training, through academia, government, community and other partnerships. Footnote 29 Materials and tools for public health communication would be less likely to reflect these pedagogical practices.

Further, recent research found that fewer than half of the master of public health programs in Canada offer courses that focus on health communication, and none specialize in health communication. Footnote 14 As with professional development, a systematic approach to enhancing communication competence in the public health workforce is needed, and master of public health programs should include targeted health communication education taught by faculty members with the relevant expertise. In addition, curricula need to be regularly reviewed to make sure they are aligned with contemporary competencies and current public health needs.

Comprehensive professional development opportunities that address contemporary public health communication needs will strengthen our capacity and ensure the availability of a skilled workforce. In contrast to current offerings in Canada, the selection of trainings in public health communication for students and practitioners in the USA is large and comprehensive. The Public Health Foundation offers the TRAIN Learning Network; the foundation and the New England Public Health Training Center have a number of courses related to communication that are mapped to the Council on Linkages’ core competencies for public health professionals. Footnote 12 Footnote 30 There are also 65 schools in the USA that, between them, offer 77 programs on health communication. Footnote 31 They could also provide a roadmap for comprehensive training and professional development aligned with core competencies and pedagogy for effective training in Canada.

Overall, the professional development offerings had strong alignment with the communication-related PHAC core competencies, with nearly half (49%) addressing all four competencies. One communication core competency, the PHAC core competency, “current technology” (#6.4), was not widely addressed by formalized offerings but had better coverage within materials and tools, although leveraging technology rather than teaching practitioners how to effectively use it tended to be mentioned. Digital technologies are vital to public health communication, as was evidenced during the COVID-19 pandemic when social media, online big data sources, data visualization, artificial intelligence and digital platforms (e.g. video conferencing software) became increasingly important. Footnote 32 Thus, it is critical that the core competencies not only reflect the scope and complexity of digital technologies that should be used by public health in communication initiatives but also that they be mapped to professional development opportunities that teach the technologies to practitioners.

As previously mentioned, the PHAC core competencies are undergoing renewal and modernization, with an estimated launch scheduled for 2024. The Chief Public Health Officer’s 2021 report identified several areas related to communication that must be addressed through the updated competencies and workforce training: addressing misinformation and disinformation; codesigning health information with communities; culturally appropriate communication; enhanced risk and crisis communication; and tailoring information to communities’ values and needs. Footnote 33 Our research found that most of the professional development offerings did not address misinformation and disinformation, although most did address tailoring communication and communicating with diverse populations. Within the context of communicating with diverse populations, however, the focus was usually on health literacy rather than on cultural competency. These results show opportunities for strengthening our professional development in areas vital to public health communication.

The Canadian public health workforce can be enhanced and supported by building stronger linkages between practice and education, including partnerships between public health schools and public health organizations and associations to co-develop and customize education and training opportunities, including specialized subdisciplines, for public health practitioners and students. Public health organizations and associations play key roles in workforce development and are aware of community-level needs and practitioner competencies through their connection to the field and monitoring and evaluating of key issues. As such, they are in the best position to clarify the public health needs of today and anticipate the needs of tomorrow. Public health schools, meanwhile, bring expertise in pedagogy and competency-based education. Such partnerships would help produce training opportunities that are tailored to organization and practitioner needs, including format, timing and focuses. Further, public health organizations and associations could provide comments and input to public health schools on what they anticipate needing in the future, which is important because of the lead time required to build curriculum and expertise in the future public health workforce.

Strengths, limitations and future research

The search strategy was designed to capture as many professional development offerings meeting our inclusion criteria as possible. The search consisted of English language results only, and some web content was inaccessible without an organization membership. Access to the full details of formalized offerings was often not possible without enrolling in the course; therefore relevant data were mostly extracted from summary information, which may have biased the results given that materials and tools often presented  information in full. Further, while formalized offerings needed to be offered within the last 12 months, materials and tools needed to be available online within the last year, but could have been published even 15 years earlier.

Our search and data retrieval processes were also limited by challenges inherent to online research. For example, broken links due to inconsistencies in Internet archival processes were common. Also, our search results may have been biased and influenced in unknown ways by Google’s algorithms. Footnote 34

With the PHAC core competencies currently being renewed, this environmental scan provides a valuable snapshot of what is available and how it corresponds to current communication core competencies within the health communication discipline of public health. This scan does not describe other professional development opportunities within other specializations or competency domains. Similar environmental scans of professional development offerings should be completed in the future and results assessed with the updated communication competencies.

The field of public health is constantly changing as a result of new knowledge from research and practice, the changing communication ecosystem and the complexity of problems facing public health practitioners. This flux is heightening the critical role of professional development opportunities for public health practitioners to build and maintain communication-related competencies. Public health core competencies guide workforce planning, job performance assessment and professional development. These competencies  are fundamental to public health capacity and contribute to improved population health.

Our findings underscore the need for more training opportunities in public health communication and a comprehensive and coordinated approach to competency-based professional development in Canada. Although the available professional development offerings are relatively well-aligned with the PHAC core competencies, misinformation and disinformation, using current technology and communication with diverse audiences are areas with far fewer opportunities for professional development. By addressing the current gaps and aligning professional development with updated competencies, public health practitioners will be able to enhance their knowledge, values, skills and behaviours for a more effective and precise public health practice.

Acknowledgements

Funding for this research was provided by the Canadian Institutes of Health Research ( CIHR ) in the form of a CIHR Catalyst Grant ( FRN 184647).

Conflicts of interest

The authors have no conflicts of interest to declare.

Authors’ contributions and statement

• MM : Conceptualization, methodology, formal analysis, funding acquisition, investigation, validation, visualization, writing – original draft, writing – review & editing.
• DM : Formal analysis, investigation, visualization, writing – original draft, writing – review & editing.
• HW : Formal analysis, investigation, methodology, writing – review & editing.
• LEG : Funding acquisition, writing – review & editing.
• AP : Funding acquisition, writing – review & editing.
• JEM : Conceptualization, formal analysis, funding acquisition, methodology, project administration, supervision, validation, writing – review & editing.

All authors have read and agreed to the published version of the manuscript.

The content and views expressed in this article are those of the authors and do not necessarily reflect those of the Government of Canada.

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