descriptive research design the first question is typically about what

• Descriptive Research Designs: Types, Examples & Methods

One of the components of research is getting enough information about the research problem—the what, how, when and where answers, which is why descriptive research is an important type of research. It is very useful when conducting research whose aim is to identify characteristics, frequencies, trends, correlations, and categories.

This research method takes a problem with little to no relevant information and gives it a befitting description using qualitative and quantitative research method s. Descriptive research aims to accurately describe a research problem.

In the subsequent sections, we will be explaining what descriptive research means, its types, examples, and data collection methods.

What is Descriptive Research?

Descriptive research is a type of research that describes a population, situation, or phenomenon that is being studied. It focuses on answering the how, what, when, and where questions If a research problem, rather than the why.

This is mainly because it is important to have a proper understanding of what a research problem is about before investigating why it exists in the first place. 

For example, an investor considering an investment in the ever-changing Amsterdam housing market needs to understand what the current state of the market is, how it changes (increasing or decreasing), and when it changes (time of the year) before asking for the why. This is where descriptive research comes in.

What Are The Types of Descriptive Research?

Descriptive research is classified into different types according to the kind of approach that is used in conducting descriptive research. The different types of descriptive research are highlighted below:

• Descriptive-survey

Descriptive survey research uses surveys to gather data about varying subjects. This data aims to know the extent to which different conditions can be obtained among these subjects.

For example, a researcher wants to determine the qualification of employed professionals in Maryland. He uses a survey as his research instrument , and each item on the survey related to qualifications is subjected to a Yes/No answer. 

This way, the researcher can describe the qualifications possessed by the employed demographics of this community. 

• Descriptive-normative survey

This is an extension of the descriptive survey, with the addition being the normative element. In the descriptive-normative survey, the results of the study should be compared with the norm.

For example, an organization that wishes to test the skills of its employees by a team may have them take a skills test. The skills tests are the evaluation tool in this case, and the result of this test is compared with the norm of each role.

If the score of the team is one standard deviation above the mean, it is very satisfactory, if within the mean, satisfactory, and one standard deviation below the mean is unsatisfactory.

• Descriptive-status

This is a quantitative description technique that seeks to answer questions about real-life situations. For example, a researcher researching the income of the employees in a company, and the relationship with their performance.

A survey will be carried out to gather enough data about the income of the employees, then their performance will be evaluated and compared to their income. This will help determine whether a higher income means better performance and low income means lower performance or vice versa.

• Descriptive-analysis

The descriptive-analysis method of research describes a subject by further analyzing it, which in this case involves dividing it into 2 parts. For example, the HR personnel of a company that wishes to analyze the job role of each employee of the company may divide the employees into the people that work at the Headquarters in the US and those that work from Oslo, Norway office.

A questionnaire is devised to analyze the job role of employees with similar salaries and who work in similar positions.

• Descriptive classification

This method is employed in biological sciences for the classification of plants and animals. A researcher who wishes to classify the sea animals into different species will collect samples from various search stations, then classify them accordingly.

• Descriptive-comparative

In descriptive-comparative research, the researcher considers 2 variables that are not manipulated, and establish a formal procedure to conclude that one is better than the other. For example, an examination body wants to determine the better method of conducting tests between paper-based and computer-based tests.

A random sample of potential participants of the test may be asked to use the 2 different methods, and factors like failure rates, time factors, and others will be evaluated to arrive at the best method.

• Correlative Survey

Correlative surveys are used to determine whether the relationship between 2 variables is positive, negative, or neutral. That is, if 2 variables say X and Y are directly proportional, inversely proportional or are not related to each other.

Examples of Descriptive Research

There are different examples of descriptive research, that may be highlighted from its types, uses, and applications. However, we will be restricting ourselves to only 3 distinct examples in this article.

• Comparing Student Performance:

An academic institution may wish 2 compare the performance of its junior high school students in English language and Mathematics. This may be used to classify students based on 2 major groups, with one group going ahead to study while courses, while the other study courses in the Arts & Humanities field.

Students who are more proficient in mathematics will be encouraged to go into STEM and vice versa. Institutions may also use this data to identify students’ weak points and work on ways to assist them.

• Scientific Classification

During the major scientific classification of plants, animals, and periodic table elements, the characteristics and components of each subject are evaluated and used to determine how they are classified.

For example, living things may be classified into kingdom Plantae or kingdom animal is depending on their nature. Further classification may group animals into mammals, pieces, vertebrae, invertebrae, etc. 

All these classifications are made a result of descriptive research which describes what they are.

• Human Behavior

When studying human behaviour based on a factor or event, the researcher observes the characteristics, behaviour, and reaction, then use it to conclude. A company willing to sell to its target market needs to first study the behaviour of the market.

This may be done by observing how its target reacts to a competitor’s product, then use it to determine their behaviour.

What are the Characteristics of Descriptive Research?  

The characteristics of descriptive research can be highlighted from its definition, applications, data collection methods, and examples. Some characteristics of descriptive research are:

• Quantitativeness

Descriptive research uses a quantitative research method by collecting quantifiable information to be used for statistical analysis of the population sample. This is very common when dealing with research in the physical sciences.

• Qualitativeness

It can also be carried out using the qualitative research method, to properly describe the research problem. This is because descriptive research is more explanatory than exploratory or experimental.

• Uncontrolled variables

In descriptive research, researchers cannot control the variables like they do in experimental research.

• The basis for further research

The results of descriptive research can be further analyzed and used in other research methods. It can also inform the next line of research, including the research method that should be used.

This is because it provides basic information about the research problem, which may give birth to other questions like why a particular thing is the way it is.

Why Use Descriptive Research Design?  

Descriptive research can be used to investigate the background of a research problem and get the required information needed to carry out further research. It is used in multiple ways by different organizations, and especially when getting the required information about their target audience.

• Define subject characteristics :

It is used to determine the characteristics of the subjects, including their traits, behaviour, opinion, etc. This information may be gathered with the use of surveys, which are shared with the respondents who in this case, are the research subjects.

For example, a survey evaluating the number of hours millennials in a community spends on the internet weekly, will help a service provider make informed business decisions regarding the market potential of the community.

• Measure Data Trends

It helps to measure the changes in data over some time through statistical methods. Consider the case of individuals who want to invest in stock markets, so they evaluate the changes in prices of the available stocks to make a decision investment decision.

Brokerage companies are however the ones who carry out the descriptive research process, while individuals can view the data trends and make decisions.

Descriptive research is also used to compare how different demographics respond to certain variables. For example, an organization may study how people with different income levels react to the launch of a new Apple phone.

This kind of research may take a survey that will help determine which group of individuals are purchasing the new Apple phone. Do the low-income earners also purchase the phone, or only the high-income earners do?

Further research using another technique will explain why low-income earners are purchasing the phone even though they can barely afford it. This will help inform strategies that will lure other low-income earners and increase company sales.

• Validate existing conditions

When you are not sure about the validity of an existing condition, you can use descriptive research to ascertain the underlying patterns of the research object. This is because descriptive research methods make an in-depth analysis of each variable before making conclusions.

• Conducted Overtime

Descriptive research is conducted over some time to ascertain the changes observed at each point in time. The higher the number of times it is conducted, the more authentic the conclusion will be.

What are the Disadvantages of Descriptive Research?  

• Response and Non-response Bias

Respondents may either decide not to respond to questions or give incorrect responses if they feel the questions are too confidential. When researchers use observational methods, respondents may also decide to behave in a particular manner because they feel they are being watched.

• The researcher may decide to influence the result of the research due to personal opinion or bias towards a particular subject. For example, a stockbroker who also has a business of his own may try to lure investors into investing in his own company by manipulating results.
• A case-study or sample taken from a large population is not representative of the whole population.
• Limited scope:The scope of descriptive research is limited to the what of research, with no information on why thereby limiting the scope of the research.

What are the Data Collection Methods in Descriptive Research?  

There are 3 main data collection methods in descriptive research, namely; observational method, case study method, and survey research.

1. Observational Method

The observational method allows researchers to collect data based on their view of the behaviour and characteristics of the respondent, with the respondents themselves not directly having an input. It is often used in market research, psychology, and some other social science research to understand human behaviour.

It is also an important aspect of physical scientific research, with it being one of the most effective methods of conducting descriptive research . This process can be said to be either quantitative or qualitative.

Quantitative observation involved the objective collection of numerical data , whose results can be analyzed using numerical and statistical methods. 

Qualitative observation, on the other hand, involves the monitoring of characteristics and not the measurement of numbers. The researcher makes his observation from a distance, records it, and is used to inform conclusions.

2. Case Study Method

A case study is a sample group (an individual, a group of people, organizations, events, etc.) whose characteristics are used to describe the characteristics of a larger group in which the case study is a subgroup. The information gathered from investigating a case study may be generalized to serve the larger group.

This generalization, may, however, be risky because case studies are not sufficient to make accurate predictions about larger groups. Case studies are a poor case of generalization.

3. Survey Research

This is a very popular data collection method in research designs. In survey research, researchers create a survey or questionnaire and distribute it to respondents who give answers.

Generally, it is used to obtain quick information directly from the primary source and also conducting rigorous quantitative and qualitative research. In some cases, survey research uses a blend of both qualitative and quantitative strategies.

Survey research can be carried out both online and offline using the following methods

• Online Surveys: This is a cheap method of carrying out surveys and getting enough responses. It can be carried out using Formplus, an online survey builder. Formplus has amazing tools and features that will help increase response rates.
• Offline Surveys: This includes paper forms, mobile offline forms , and SMS-based forms.

What Are The Differences Between Descriptive and Correlational Research?  

Before going into the differences between descriptive and correlation research, we need to have a proper understanding of what correlation research is about. Therefore, we will be giving a summary of the correlation research below.

Correlational research is a type of descriptive research, which is used to measure the relationship between 2 variables, with the researcher having no control over them. It aims to find whether there is; positive correlation (both variables change in the same direction), negative correlation (the variables change in the opposite direction), or zero correlation (there is no relationship between the variables).

Correlational research may be used in 2 situations;

(i) when trying to find out if there is a relationship between two variables, and

(ii) when a causal relationship is suspected between two variables, but it is impractical or unethical to conduct experimental research that manipulates one of the variables. 

Below are some of the differences between correlational and descriptive research:

• Definitions :

Descriptive research aims is a type of research that provides an in-depth understanding of the study population, while correlational research is the type of research that measures the relationship between 2 variables. 

• Characteristics :

Descriptive research provides descriptive data explaining what the research subject is about, while correlation research explores the relationship between data and not their description.

• Predictions :

 Predictions cannot be made in descriptive research while correlation research accommodates the possibility of making predictions.

Descriptive Research vs. Causal Research

Descriptive research and causal research are both research methodologies, however, one focuses on a subject’s behaviors while the latter focuses on a relationship’s cause-and-effect. To buttress the above point, descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular or specific population or situation. 

It focuses on providing an accurate and detailed account of an already existing state of affairs between variables. Descriptive research answers the questions of “what,” “where,” “when,” and “how” without attempting to establish any causal relationships or explain any underlying factors that might have caused the behavior.

Causal research, on the other hand, seeks to determine cause-and-effect relationships between variables. It aims to point out the factors that influence or cause a particular result or behavior. Causal research involves manipulating variables, controlling conditions or a subgroup, and observing the resulting effects. The primary objective of causal research is to establish a cause-effect relationship and provide insights into why certain phenomena happen the way they do.

Descriptive Research vs. Analytical Research

Descriptive research provides a detailed and comprehensive account of a specific situation or phenomenon. It focuses on describing and summarizing data without making inferences or attempting to explain underlying factors or the cause of the factor. 

It is primarily concerned with providing an accurate and objective representation of the subject of research. While analytical research goes beyond the description of the phenomena and seeks to analyze and interpret data to discover if there are patterns, relationships, or any underlying factors. 

It examines the data critically, applies statistical techniques or other analytical methods, and draws conclusions based on the discovery. Analytical research also aims to explore the relationships between variables and understand the underlying mechanisms or processes involved.

Descriptive Research vs. Exploratory Research

Descriptive research is a research method that focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. This type of research describes the characteristics, behaviors, or relationships within the given context without looking for an underlying cause. 

Descriptive research typically involves collecting and analyzing quantitative or qualitative data to generate descriptive statistics or narratives. Exploratory research differs from descriptive research because it aims to explore and gain firsthand insights or knowledge into a relatively unexplored or poorly understood topic. 

It focuses on generating ideas, hypotheses, or theories rather than providing definitive answers. Exploratory research is often conducted at the early stages of a research project to gather preliminary information and identify key variables or factors for further investigation. It involves open-ended interviews, observations, or small-scale surveys to gather qualitative data.

Read More – Exploratory Research: What are its Method & Examples?

Descriptive Research vs. Experimental Research

Descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular population or situation. It focuses on providing an accurate and detailed account of the existing state of affairs. 

Descriptive research typically involves collecting data through surveys, observations, or existing records and analyzing the data to generate descriptive statistics or narratives. It does not involve manipulating variables or establishing cause-and-effect relationships.

Experimental research, on the other hand, involves manipulating variables and controlling conditions to investigate cause-and-effect relationships. It aims to establish causal relationships by introducing an intervention or treatment and observing the resulting effects. 

Experimental research typically involves randomly assigning participants to different groups, such as control and experimental groups, and measuring the outcomes. It allows researchers to control for confounding variables and draw causal conclusions.

Related – Experimental vs Non-Experimental Research: 15 Key Differences

Descriptive Research vs. Explanatory Research

Descriptive research focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. It aims to describe the characteristics, behaviors, or relationships within the given context. 

Descriptive research is primarily concerned with providing an objective representation of the subject of study without explaining underlying causes or mechanisms. Explanatory research seeks to explain the relationships between variables and uncover the underlying causes or mechanisms. 

It goes beyond description and aims to understand the reasons or factors that influence a particular outcome or behavior. Explanatory research involves analyzing data, conducting statistical analyses, and developing theories or models to explain the observed relationships.

Descriptive Research vs. Inferential Research

Descriptive research focuses on describing and summarizing data without making inferences or generalizations beyond the specific sample or population being studied. It aims to provide an accurate and objective representation of the subject of study. 

Descriptive research typically involves analyzing data to generate descriptive statistics, such as means, frequencies, or percentages, to describe the characteristics or behaviors observed.

Inferential research, however, involves making inferences or generalizations about a larger population based on a smaller sample. 

It aims to draw conclusions about the population characteristics or relationships by analyzing the sample data. Inferential research uses statistical techniques to estimate population parameters, test hypotheses, and determine the level of confidence or significance in the findings.

Related – Inferential Statistics: Definition, Types + Examples

Conclusion  

The uniqueness of descriptive research partly lies in its ability to explore both quantitative and qualitative research methods. Therefore, when conducting descriptive research, researchers have the opportunity to use a wide variety of techniques that aids the research process.

Descriptive research explores research problems in-depth, beyond the surface level thereby giving a detailed description of the research subject. That way, it can aid further research in the field, including other research methods .

It is also very useful in solving real-life problems in various fields of social science, physical science, and education.

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Child Care and Early Education Research Connections

Descriptive research studies.

Descriptive research is a type of research that is used to describe the characteristics of a population. It collects data that are used to answer a wide range of what, when, and how questions pertaining to a particular population or group. For example, descriptive studies might be used to answer questions such as: What percentage of Head Start teachers have a bachelor's degree or higher? What is the average reading ability of 5-year-olds when they first enter kindergarten? What kinds of math activities are used in early childhood programs? When do children first receive regular child care from someone other than their parents? When are children with developmental disabilities first diagnosed and when do they first receive services? What factors do programs consider when making decisions about the type of assessments that will be used to assess the skills of the children in their programs? How do the types of services children receive from their early childhood program change as children age?

Descriptive research does not answer questions about why a certain phenomenon occurs or what the causes are. Answers to such questions are best obtained from  randomized and quasi-experimental studies . However, data from descriptive studies can be used to examine the relationships (correlations) among variables. While the findings from correlational analyses are not evidence of causality, they can help to distinguish variables that may be important in explaining a phenomenon from those that are not. Thus, descriptive research is often used to generate hypotheses that should be tested using more rigorous designs.

A variety of data collection methods may be used alone or in combination to answer the types of questions guiding descriptive research. Some of the more common methods include surveys, interviews, observations, case studies, and portfolios. The data collected through these methods can be either quantitative or qualitative. Quantitative data are typically analyzed and presenting using  descriptive statistics . Using quantitative data, researchers may describe the characteristics of a sample or population in terms of percentages (e.g., percentage of population that belong to different racial/ethnic groups, percentage of low-income families that receive different government services) or averages (e.g., average household income, average scores of reading, mathematics and language assessments). Quantitative data, such as narrative data collected as part of a case study, may be used to organize, classify, and used to identify patterns of behaviors, attitudes, and other characteristics of groups.

Descriptive studies have an important role in early care and education research. Studies such as the  National Survey of Early Care and Education  and the  National Household Education Surveys Program  have greatly increased our knowledge of the supply of and demand for child care in the U.S. The  Head Start Family and Child Experiences Survey  and the  Early Childhood Longitudinal Study Program  have provided researchers, policy makers and practitioners with rich information about school readiness skills of children in the U.S.

Each of the methods used to collect descriptive data have their own strengths and limitations. The following are some of the strengths and limitations of descriptive research studies in general.

Study participants are questioned or observed in a natural setting (e.g., their homes, child care or educational settings).

Study data can be used to identify the prevalence of particular problems and the need for new or additional services to address these problems.

Descriptive research may identify areas in need of additional research and relationships between variables that require future study. Descriptive research is often referred to as "hypothesis generating research."

Depending on the data collection method used, descriptive studies can generate rich datasets on large and diverse samples.

Limitations:

Descriptive studies cannot be used to establish cause and effect relationships.

Respondents may not be truthful when answering survey questions or may give socially desirable responses.

The choice and wording of questions on a questionnaire may influence the descriptive findings.

Depending on the type and size of sample, the findings may not be generalizable or produce an accurate description of the population of interest.

• What is descriptive research?

Last updated

5 February 2023

Reviewed by

Cathy Heath

Descriptive research is a common investigatory model used by researchers in various fields, including social sciences, linguistics, and academia.

Read on to understand the characteristics of descriptive research and explore its underlying techniques, processes, and procedures.

Analyze your descriptive research

Dovetail streamlines analysis to help you uncover and share actionable insights

Descriptive research is an exploratory research method. It enables researchers to precisely and methodically describe a population, circumstance, or phenomenon.

As the name suggests, descriptive research describes the characteristics of the group, situation, or phenomenon being studied without manipulating variables or testing hypotheses . This can be reported using surveys , observational studies, and case studies. You can use both quantitative and qualitative methods to compile the data.

Besides making observations and then comparing and analyzing them, descriptive studies often develop knowledge concepts and provide solutions to critical issues. It always aims to answer how the event occurred, when it occurred, where it occurred, and what the problem or phenomenon is.

• Characteristics of descriptive research

The following are some of the characteristics of descriptive research:

Quantitativeness

Descriptive research can be quantitative as it gathers quantifiable data to statistically analyze a population sample. These numbers can show patterns, connections, and trends over time and can be discovered using surveys, polls, and experiments.

Qualitativeness

Descriptive research can also be qualitative. It gives meaning and context to the numbers supplied by quantitative descriptive research .

Researchers can use tools like interviews, focus groups, and ethnographic studies to illustrate why things are what they are and help characterize the research problem. This is because it’s more explanatory than exploratory or experimental research.

Uncontrolled variables

Descriptive research differs from experimental research in that researchers cannot manipulate the variables. They are recognized, scrutinized, and quantified instead. This is one of its most prominent features.

Cross-sectional studies

Descriptive research is a cross-sectional study because it examines several areas of the same group. It involves obtaining data on multiple variables at the personal level during a certain period. It’s helpful when trying to understand a larger community’s habits or preferences.

Carried out in a natural environment

Descriptive studies are usually carried out in the participants’ everyday environment, which allows researchers to avoid influencing responders by collecting data in a natural setting. You can use online surveys or survey questions to collect data or observe.

Basis for further research

You can further dissect descriptive research’s outcomes and use them for different types of investigation. The outcomes also serve as a foundation for subsequent investigations and can guide future studies. For example, you can use the data obtained in descriptive research to help determine future research designs.

• Descriptive research methods

There are three basic approaches for gathering data in descriptive research: observational, case study, and survey.

You can use surveys to gather data in descriptive research. This involves gathering information from many people using a questionnaire and interview .

Surveys remain the dominant research tool for descriptive research design. Researchers can conduct various investigations and collect multiple types of data (quantitative and qualitative) using surveys with diverse designs.

You can conduct surveys over the phone, online, or in person. Your survey might be a brief interview or conversation with a set of prepared questions intended to obtain quick information from the primary source.

Observation

This descriptive research method involves observing and gathering data on a population or phenomena without manipulating variables. It is employed in psychology, market research , and other social science studies to track and understand human behavior.

Observation is an essential component of descriptive research. It entails gathering data and analyzing it to see whether there is a relationship between the two variables in the study. This strategy usually allows for both qualitative and quantitative data analysis.

Case studies

A case study can outline a specific topic’s traits. The topic might be a person, group, event, or organization.

It involves using a subset of a larger group as a sample to characterize the features of that larger group.

You can generalize knowledge gained from studying a case study to benefit a broader audience.

This approach entails carefully examining a particular group, person, or event over time. You can learn something new about the study topic by using a small group to better understand the dynamics of the entire group.

• Types of descriptive research

There are several types of descriptive study. The most well-known include cross-sectional studies, census surveys, sample surveys, case reports, and comparison studies.

Case reports and case series

In the healthcare and medical fields, a case report is used to explain a patient’s circumstances when suffering from an uncommon illness or displaying certain symptoms. Case reports and case series are both collections of related cases. They have aided the advancement of medical knowledge on countless occasions.

The normative component is an addition to the descriptive survey. In the descriptive–normative survey, you compare the study’s results to the norm.

Descriptive survey

This descriptive type of research employs surveys to collect information on various topics. This data aims to determine the degree to which certain conditions may be attained.

You can extrapolate or generalize the information you obtain from sample surveys to the larger group being researched.

Correlative survey

Correlative surveys help establish if there is a positive, negative, or neutral connection between two variables.

Performing census surveys involves gathering relevant data on several aspects of a given population. These units include individuals, families, organizations, objects, characteristics, and properties.

During descriptive research, you gather different degrees of interest over time from a specific population. Cross-sectional studies provide a glimpse of a phenomenon’s prevalence and features in a population. There are no ethical challenges with them and they are quite simple and inexpensive to carry out.

Comparative studies

These surveys compare the two subjects’ conditions or characteristics. The subjects may include research variables, organizations, plans, and people.

Comparison points, assumption of similarities, and criteria of comparison are three important variables that affect how well and accurately comparative studies are conducted.

For instance, descriptive research can help determine how many CEOs hold a bachelor’s degree and what proportion of low-income households receive government help.

• Pros and cons

The primary advantage of descriptive research designs is that researchers can create a reliable and beneficial database for additional study. To conduct any inquiry, you need access to reliable information sources that can give you a firm understanding of a situation.

Quantitative studies are time- and resource-intensive, so knowing the hypotheses viable for testing is crucial. The basic overview of descriptive research provides helpful hints as to which variables are worth quantitatively examining. This is why it’s employed as a precursor to quantitative research designs.

Some experts view this research as untrustworthy and unscientific. However, there is no way to assess the findings because you don’t manipulate any variables statistically.

Cause-and-effect correlations also can’t be established through descriptive investigations. Additionally, observational study findings cannot be replicated, which prevents a review of the findings and their replication.

The absence of statistical and in-depth analysis and the rather superficial character of the investigative procedure are drawbacks of this research approach.

• Descriptive research examples and applications

Several descriptive research examples are emphasized based on their types, purposes, and applications. Research questions often begin with “What is …” These studies help find solutions to practical issues in social science, physical science, and education.

Here are some examples and applications of descriptive research:

Determining consumer perception and behavior

Organizations use descriptive research designs to determine how various demographic groups react to a certain product or service.

For example, a business looking to sell to its target market should research the market’s behavior first. When researching human behavior in response to a cause or event, the researcher pays attention to the traits, actions, and responses before drawing a conclusion.

Scientific classification

Scientific descriptive research enables the classification of organisms and their traits and constituents.

Measuring data trends

A descriptive study design’s statistical capabilities allow researchers to track data trends over time. It’s frequently used to determine the study target’s current circumstances and underlying patterns.

Conduct comparison

Organizations can use a descriptive research approach to learn how various demographics react to a certain product or service. For example, you can study how the target market responds to a competitor’s product and use that information to infer their behavior.

• Bottom line

A descriptive research design is suitable for exploring certain topics and serving as a prelude to larger quantitative investigations. It provides a comprehensive understanding of the “what” of the group or thing you’re investigating.

This research type acts as the cornerstone of other research methodologies . It is distinctive because it can use quantitative and qualitative research approaches at the same time.

What is descriptive research design?

Descriptive research design aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why.

How does descriptive research compare to qualitative research?

Despite certain parallels, descriptive research concentrates on describing phenomena, while qualitative research aims to understand people better.

How do you analyze descriptive research data?

Data analysis involves using various methodologies, enabling the researcher to evaluate and provide results regarding validity and reliability.

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• Knowledge Base
• Methodology

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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Introducing Research Designs

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We define research design as a combination of decisions within a research process. These decisions enable us to make a specific argument by answering the research question. The implementation plan for the research study allows for reaching the desired (type of) conclusion. Different research designs make it possible to draw different conclusions. These conclusions produce various kinds of intellectual contributions. As all kinds of intellectual contributions are necessary to increase the body of knowledge, no research design is inherently better than another, only more appropriate to answer a specific question.

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Methodology

• Types of Research Designs Compared | Guide & Examples

Types of Research Designs Compared | Guide & Examples

Published on June 20, 2019 by Shona McCombes . Revised on June 22, 2023.

When you start planning a research project, developing research questions and creating a  research design , you will have to make various decisions about the type of research you want to do.

There are many ways to categorize different types of research. The words you use to describe your research depend on your discipline and field. In general, though, the form your research design takes will be shaped by:

• The type of knowledge you aim to produce
• The type of data you will collect and analyze
• The sampling methods , timescale and location of the research

This article takes a look at some common distinctions made between different types of research and outlines the key differences between them.

Table of contents

Types of research aims, types of research data, types of sampling, timescale, and location, other interesting articles.

The first thing to consider is what kind of knowledge your research aims to contribute.

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The next thing to consider is what type of data you will collect. Each kind of data is associated with a range of specific research methods and procedures.

Finally, you have to consider three closely related questions: how will you select the subjects or participants of the research? When and how often will you collect data from your subjects? And where will the research take place?

Keep in mind that the methods that you choose bring with them different risk factors and types of research bias . Biases aren’t completely avoidable, but can heavily impact the validity and reliability of your findings if left unchecked.

Choosing between all these different research types is part of the process of creating your research design , which determines exactly how your research will be conducted. But the type of research is only the first step: next, you have to make more concrete decisions about your research methods and the details of the study.

Read more about creating a research design

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

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Descriptive Research in Psychology

Sometimes you need to dig deeper than the pure statistics

John Loeppky is a freelance journalist based in Regina, Saskatchewan, Canada, who has written about disability and health for outlets of all kinds.

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Types of Descriptive Research and the Methods Used

• Advantages & Limitations of Descriptive Research

Best Practices for Conducting Descriptive Research

Descriptive research is one of the key tools needed in any psychology researcher’s toolbox in order to create and lead a project that is both equitable and effective. Because psychology, as a field, loves definitions, let’s start with one. The University of Minnesota’s Introduction to Psychology defines this type of research as one that is “...designed to provide a snapshot of the current state of affairs.” That's pretty broad, so what does that mean in practice? Dr. Heather Derry-Vick (PhD) , an assistant professor in psychiatry at Hackensack Meridian School of Medicine, helps us put it into perspective. "Descriptive research really focuses on defining, understanding, and measuring a phenomenon or an experience," she says. "Not trying to change a person's experience or outcome, or even really looking at the mechanisms for why that might be happening, but more so describing an experience or a process as it unfolds naturally.”

Within the descriptive research methodology there are multiple types, including the following.

Descriptive Survey Research

This involves going beyond a typical tool like a LIkert Scale —where you typically place your response to a prompt on a one to five scale. We already know that scales like this can be ineffective, particularly when studying pain, for example.

When that's the case, using a descriptive methodology can help dig deeper into how a person is thinking, feeling, and acting rather than simply quantifying it in a way that might be unclear or confusing.

Descriptive Observational Research

Think of observational research like an ethically-focused version of people-watching. One example would be watching the patterns of children on a playground—perhaps when looking at a concept like risky play or seeking to observe social behaviors between children of different ages.

Descriptive Case Study Research

A descriptive approach to a case study is akin to a biography of a person, honing in on the experiences of a small group to extrapolate to larger themes. We most commonly see descriptive case studies when those in the psychology field are using past clients as an example to illustrate a point.

Correlational Descriptive Research

While descriptive research is often about the here and now, this form of the methodology allows researchers to make connections between groups of people. As an example from her research, Derry-Vick says she uses this method to identify how gender might play a role in cancer scan anxiety, aka scanxiety.

Dr. Derry-Vick's research uses surveys and interviews to get a sense of how cancer patients are feeling and what they are experiencing both in the course of their treatment and in the lead-up to their next scan, which can be a significant source of stress.

David Marlon, PsyD, MBA , who works as a clinician and as CEO at Vegas Stronger, and whose research focused on leadership styles at community-based clinics, says that using descriptive research allowed him to get beyond the numbers.

In his case, that includes data points like how many unhoused people found stable housing over a certain period or how many people became drug-free—and identify the reasons for those changes.

Those [data points] are some practical, quantitative tools that are helpful. But when I question them on how safe they feel, when I question them on the depth of the bond or the therapeutic alliance, when I talk to them about their processing of traumas,  wellbeing...these are things that don't really fall on to a yes, no, or even on a Likert scale.

For the portion of his thesis that was focused on descriptive research, Marlon used semi-structured interviews to look at the how and the why of transformational leadership and its impact on clinics’ clients and staff.

Advantages & Limitations of Descriptive Research

So, if the advantages of using descriptive research include that it centers the research participants, gives us a clear picture of what is happening to a person in a particular moment,  and gives us very nuanced insights into how a particular situation is being perceived by the very person affected, are there drawbacks? Yes, there are. Dr. Derry-Vick says that it’s important to keep in mind that just because descriptive research tells us something is happening doesn’t mean it necessarily leads us to the resolution of a given problem.

I think that, by design, the descriptive research might not tell you why a phenomenon is happening. So it might tell you, very well, how often it's happening, or what the levels are, or help you understand it in depth. But that may or may not always tell you information about the causes or mechanisms for why something is happening.

Another limitation she identifies is that it also can’t tell you, on its own, whether a particular treatment pathway is having the desired effect.

“Descriptive research in and of itself can't really tell you whether a specific approach is going to be helpful until you take in a different approach to actually test it.”

Marlon, who believes in a multi-disciplinary approach, says that his subfield—addictions—is one where descriptive research had its limits, but helps readers go beyond preconceived notions of what addictions treatment looks and feels like when it is effective. “If we talked to and interviewed and got descriptive information from the clinicians and the clients, a much more precise picture would be painted, showing the need for a client's specific multidisciplinary approach augmented with a variety of modalities," he says. "If you tried to look at my discipline in a pure quantitative approach , it wouldn't begin to tell the real story.”

Because you’re controlling far fewer variables than other forms of research, it’s important to identify whether those you are describing, your study participants, should be informed that they are part of a study.

For example, if you’re observing and describing who is buying what in a grocery store to identify patterns, then you might not need to identify yourself.

However, if you’re asking people about their fear of certain treatment, or how their marginalized identities impact their mental health in a particular way, there is far more of a pressure to think deeply about how you, as the researcher, are connected to the people you are researching.

Many descriptive research projects use interviews as a form of research gathering and, as a result, descriptive research that is focused on this type of data gathering also has ethical and practical concerns attached. Thankfully, there are plenty of guides from established researchers about how to best conduct these interviews and/or formulate surveys .

While descriptive research has its limits, it is commonly used by researchers to get a clear vantage point on what is happening in a given situation.

Tools like surveys, interviews, and observation are often employed to dive deeper into a given issue and really highlight the human element in psychological research. At its core, descriptive research is rooted in a collaborative style that allows deeper insights when used effectively.

University of Minnesota. Introduction to Psychology .

By John Loeppky John Loeppky is a freelance journalist based in Regina, Saskatchewan, Canada, who has written about disability and health for outlets of all kinds.

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Descriptive Research Design

• September 29, 2021

Voxco’s Descriptive Research guide helps uncover the how, when, what, and where questions in a research problem

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When conducting a study, researchers generally try to find an explanation for the existence of a phenomenon. They want to understand “why” the phenomenon occurred. 

However, before identifying why a phenomenon occurred, it is integral to answer other questions first. You need to have answers to the “what,” “when,” “how,” and “where” before you can understand the “why.” This is where descriptive research comes in.

The descriptive research design involves using a range of qualitative and quantitative research methods to collect data that aids in accurately describing a research problem.

What is Descriptive Research Design?

Descriptive research design is a type of research design that aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why. 

A researcher can conduct this research using various methodologies. It predominantly employs quantitative data, although qualitative data is sometimes used for descriptive purposes. 

It is important to note that in the descriptive research method, the researcher does not control or manipulate any variables, unlike in experimental research. Instead, the variables are only identified, observed, and measured. 

Surveys and observation are the most used method to conduct this research design. You can leverage online survey tools or offline survey tools to gather data as per your research objective.

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What are the Characteristics of Descriptive Research Design?

Let’s take a look at the defining characteristics of the descriptive research design:

1. Quantitative in nature 

Descriptive research involves the collection of quantifiable and systematic data that can be used for the statistical analysis of the research problem. 

2. Uncontrolled variables

One of the most prominent characteristics of descriptive research is that, unlike in experimental research, the variables are not controlled or manipulated. Instead, they are simply identified, observed, and measured.

3. A basis for further research

The data collected in descriptive research provides a base for further research as it helps obtain a comprehensive understanding of the research question so that it can be answered appropriately. 

4. Cross-sectional studies

The descriptive research method is generally carried out through cross-sectional studies. A cross-sectional study is a type of observational study that involves gathering information on various variables at the individual level at a given point in time.

Example of Descriptive Research Design

To gain a deeper understanding of the descriptive method of research, let’s consider the following descriptive design research example: 

Company XYZ is a girls’ shoe brand catering to girls, specifically between the ages of 4 to 14. 

They want to start selling shoes for boys of the same age group as well and therefore want to gather information on the kind of shoes boys want to wear. They decide to conduct market research & choose the observational method to learn about different shoes boys wear nowadays. 

Naturalistic observation can be conducted by observing boys’ shoes in schools, malls, playgrounds, and other public spaces. 

This will help company XYZ identify the kind of shoe boys wear nowadays so that they can create the kind of products that will appeal to this audience.

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Why use Descriptive Research Design?

A descriptive approach to research allows researchers to thoroughly investigate the background of a research problem before further research can be carried out. It can be used in social science research to explore and document the nature and scope of a problem, to identify trends and patterns, and to provide a basis for subsequent research. 

The findings of descriptive research can help inform decision-making, policy development, and program planning.

There are many different contexts in which the use of a descriptive research design is beneficial. Here are some important uses of descriptive research design:

1. To measure data trends 

The descriptive method of research can be used to measure changes in variables over a period of time, allowing trends to be identified and analyzed. 

2. To compare variables

Descriptive research can be used to compare different variables and how different demographics respond to different variables. 

3. To define the characteristics of subjects

It can also be used to determine the different characteristics of the subjects. This can include characteristics such as opinions, traits, behavior, etc. 

4. To verify or validate existing conditions 

Descriptive research can prove to be a useful tool when trying to test the validity of an existing condition as it involves conducting an in-depth analysis of every variable before drawing conclusions.

What Are Some Examples of Descriptive Research Questions?

Here are some examples of descriptive research questions that can be addressed using a descriptive research design include:

• What are the demographic characteristics of a particular population?
• What is the prevalence of a particular health condition or risk factor?
• What are the attitudes and beliefs of a particular group towards a particular issue?
• What are the behaviors and experiences of individuals who have been exposed to a particular intervention or treatment?

What Are the Advantages of Descriptive Research Design?

The following are a few advantages of using a descriptive research design: 

1. Multiple methods of data collection

Research can use a wide range of methods for data collection, such as case studies, observational, and survey methods. They can also decide how they want to collect the data, online, offline, or via phone. 

2. Fast and cost-effective

As the descriptive research design often employs the use of surveys, data can be collected from a very large sample size quickly and cost-effectively. 

Researchers aiming to conduct market research using this research design should leverage integrated market research software . It will enable them to conduct product, customer, brand, and market research using suitable channels. 

3. Comprehensive

Descriptive research often uses quantitative and qualitative research in amalgamation, providing a more holistic understanding of the research topic. 

4. External validity

Results obtained through the descriptive method of research often have high external validity as research is conducted in the respondent’s natural environment and no variables are manipulated.

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What Are the Disadvantages of Descriptive Research Design?

The following are a few disadvantages of using a descriptive research design:

1. Cannot test or verify the research question

The descriptive method of research cannot be used to test or verify the research problem as the data collected does not help explain the cause of the phenomena being studied. 

2. Lack of reliability

If the research problem isn’t formulated well, then the data collected may not be entirely reliable. This also makes it more tedious to carry out a credible investigation. 

3. Risk of untrue responses

Descriptive research relies on the responses of people, especially when conducted using surveys. There may be instances when people provide false responses, compromising the validity of the data collected and the research results. 

4. Risk of sampling error

The descriptive research method generally employs random sampling while selecting a sample group. The randomness may lead to sampling error if the sample group isn’t representative of the larger population. Sampling error would lead to unreliable and inaccurate results.

What Are the Different Methods of Descriptive Research Design?

There are three most important descriptive research design methods:

In survey research, questionnaires or polls are used to collect information on a specific topic from respondents. Surveys should involve a mix of closed-ended and open-ended questions, as both have their own advantages. 

Online survey tools allow multiple data collection channels such as email, website, and SMS surveys. 

They are also popularly used in market research to collect customer feedback to optimize products and strategies and improve customer experience (CX). Some popular market research surveys are Net Promoter Score® (NPS®) surveys , brand tracking surveys , and conjoint analysis surveys . 

2. Case Studies 

The case study method involves the in-depth research of individuals or groups of individuals. Case studies involve gathering detailed data on a narrowly defined subject rather than gathering a large volume of data to identify correlations and patterns. 

Therefore, this method is often used to describe a specific subject’s different characteristics rather than generalizable facts. 

Case studies allow researchers to create hypotheses that can widen the scope of evaluation while studying the phenomenon. However, it is important to note that case studies cannot be used to outline the cause-and-effect relationship between variables as they cannot make accurate predictions due to the risk of researcher bias.

3. Observations method

In this method, researchers observe respondents in their natural environment, from a distance, and therefore do not influence the variables being studied. This allows them to gather information on the behaviors and characteristics being studied without having to rely on respondents for honest and accurate responses. 

The observational method is considered the most effective method for carrying out descriptive research. It involves the collection of both qualitative and quantitative data. You can leverage offline survey tools to gather data digitally, even without the Internet. 

Quantitative observation should be related to or understood in terms of quantity and can be analyzed with the use of statistical data analysis methods. A few examples of quantitative observations include age, weight, height, etc. 

Qualitative observations, on the other hand, involve monitoring variables whose values do not need to be related to numerical measurements. 

When employing this research method, the researcher can choose to be a complete observer, an observer as a participant, a participant as an observer, or a full participant. 

The observational method is generally used in psychological, social, and market research to obtain data that explains how people behave in real-life settings.

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What Are the Types of Descriptive Research Design Surveys?

The following are the different types of descriptive survey studies:

1. Census survey

A census survey is a kind of survey where information is gathered from all units of a population. Data collected through a census study is highly generalizable to the population as all or most units of the population are sampled. 

2. Sample survey 

A sample survey involves gathering information from a small subgroup of the entire population. When selecting a sample, the aim is to select a group of individuals representing the target population so that the data collected can be generalized to the larger population. Sample groups allow research to be conducted in a fast and cost-effective way. 

3. Cross-sectional survey 

In this type of survey, standardized data is collected from a cross-section of the pre-determined population at a given point in time. There are two main types of cross-sectional surveys ; those with a single variable and those with two or more variables. 

4. Longitudinal survey

Longitudinal surveys are used in longitudinal studies where the same variables are observed over a long period of time. This allows researchers to investigate the status of variables at different points in time. There are three main types of longitudinal studies ; trend, panel, and cohort.

5. Comparative survey

Comparative surveys are used to compare the status of two or more variables. The variables are compared using specific criteria that must be delineated as criterion variables. 

6. Evaluative survey

An evaluative survey is generally used to evaluate a program, policy, or curriculum. It involves gathering information that can be used to rate the effectiveness and worthwhileness of a program or policy, or institution. 

7. Documentary survey

A documentary survey involves gathering and analyzing information using pre-existing data that is already available. This data can be research papers, review articles, books, official records, etc. In documentary studies, the researcher evaluates the available literature on the research topic.

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How to Conduct a Descriptive Research Design

Use the following steps to conduct a study using the descriptive method of research:

Step-1: Outline the research objective

The first step is to identify and outline the objectives of your research and then translate these objectives into criteria of investigation. You must clearly identify the different issues and questions in the context of which the knowledge of the situation must be surveyed. 

This must be framed in the form of objectives. Once you’ve clearly stated your criteria and objectives, you must also specify the nature of the data that must be gathered. 

Step-2: Determine the tools and techniques to be used for data collection

In this step, you must determine the tools you will employ for the data collection process. Some examples of different tools that can be used are interviews, questionnaires, observation schedules, reaction scales, etc. 

In this stage, you will have to identify which tools and techniques are relevant and valid to your study. Leverage robust survey software that offers you multiple channels, thus enabling you to utilize various channels to gather insights. 

Step-3: Define​​ the target population and sample group

In the fourth step, you will have to outline your target population. The target population is the group of individuals that you are examining in your research study. Additionally, unless you are conducting a census study and collecting data from the entire population, you must select a sample group.

You can also use an audience panel to accelerate your research. A survey panel gives you access to diverse respondents so you can create your ideal panel. 

Additional read: Types of sampling methods .

Step-4: Select a method for data collection

In the data collection stage, you must have a clear plan of how your data will be collected. This involves clearly outlining the type of data you require, the tools that will be used to gather it, the level of training required by researchers to collect the data, the time required for data collection and fieldwork, and so on. 

As you collect data, keep your research question and objectives in mind and aim to gather authentic and objective data without personal bias. 

Step-5: Analyse the data collected

Once you’ve collected your data, you reach the sixth stage of descriptive research: data analysis. In this stage, you will have to evaluate all the data collected from all your different sources, quantify and qualify them, and then categorize them component-wise. 

If you are working with quantitative and qualitative data, you must employ a range of different quantitative and qualitative analysis techniques to analyze the data collected. 

Leverage survey analytics software that allows you to run statistical analysis and observe data on a live dashboard.  

Step-6: Write the report

The final step of survey research involves writing the report. As survey research involves working with extensive data, it is important to keep the focus of the investigation in mind. The report must be precise and objective-oriented.

Why Use Voxco for Descriptive Research Design?

Voxco being an omnichannel survey software , can be a valuable tool in descriptive research design. It can provide its users with a convenient and efficient means of collecting data from a large number of respondents. 

It allows researchers to design and distribute surveys to a targeted sample of participants, collect data in a standardized format, and analyze the results.

Here are some ways in which Voxco helps with descriptive research design:

• Customizable surveys: Voxco lets its users design surveys with a range of question types and themes. 
• Ease of distribution: With a range of distribution integration, Voxco makes it easy for users to distribute surveys easily via email, SMS, social media, etc. It helps the surveys reach a larger number of respondents. 
• Data analysis: Voxco not only helps researchers gather survey data but also analyzes the survey feedback, which allows researchers to get actionable insights on a visual dashboard. 

Overall, Voxco survey software is an effective tool for conducting descriptive research design, as it provides a streamlined and efficient way to gather, measure, and analyze survey data.

Wondering what will be the cost of conducting a survey using Voxco?

This sums up our article on descriptive research design. This research method helps uncover the hidden element of a customer’s behavior. It helps you create a foundation for your research by helping you create an outline of your research subject.

Begin your descriptive research with a free step-by-step guide to descriptive research

What is descriptive research?

Descriptive research design is a type of research methodology that researchers mostly use to analyze and document the behaviors and characteristics of a particular group of people. It gives a detailed analysis of a situation to explore the relation between two variables.

What is descriptive research study used for?

A descriptive research study is a type of observational research and is used for exploring and documenting the nature and scope of a problem, identifying its trends and patterns, and providing a basis for subsequent research. The outcome of a descriptive study is helpful in making decisions, developing policies, and planning social programs.

It is primarily concerned with describing the current state of a given phenomenon rather than explaining why it exists or how it came to be.

Why is descriptive research design used?

Descriptive research design can be used for a variety of reasons, including

• To describe and document a phenomenon of a particular population
• To identify patterns and trends
• To generate hypotheses for further research
• To inform decision-making and policy development

What is an example of a descriptive method?

A case study that examines the experiences of a small business run by women can be an example of a descriptive method of research. Let’s 

For instance, a researcher may conduct a case study of a small business solely run by women that have successfully implemented sustainable business practices in their food cloth manufacturing business. 

The case study could involve interviews with the owners of the business, observation of their business practices, and analysis of their financial data to document the costs and benefits of sustainability initiatives.

The researchers can then use the findings of the case study to provide a detailed account of the business’s approach to sustainability and to identify best practices that could be applied to other businesses.

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Principles of Sociological Inquiry

Chapter 5: research design, chapter 5 research design, how to design a research project.

Now that you’ve figured out what to study, you need to figure out how to study it. Your library research can help in this regard. Reading published studies is a great way to familiarize yourself with the various components of a research project. It will also bring to your attention some of the major considerations to keep in mind when designing a research project. We’ll say more about reviewing the literature near the end of this chapter, but we’ll begin with a focus on research design. We’ll discuss the decisions you need to make about the goals of your research, the major components of a research project, along with a few additional aspects of designing research.

5.1 Goals of the Research Project

Learning objectives.

• Understand and describe the differences among exploratory, descriptive, and explanatory research.
• Define and provide an example of idiographic research.
• Define and provide an example of nomothetic research.
• Identify circumstances under which research would be defined as applied and compare those to circumstances under which research would be defined as basic.

A recent news story about college students’ addictions to electronic gadgets (Lisk, 2011) Lisk, J. (2011). Addiction to our electronic gadgets. Retrieved from http://www.cnn.com/video/#/video/health/2011/03/01/hm.election.addiction.cnn?iref=allsearch describes findings from some current research by Professor Susan Moeller and colleagues from the University of Maryland ( http://withoutmedia.wordpress.com ). The story raises a number of interesting questions. Just what sorts of gadgets are students addicted to? How do these addictions work? Why do they exist, and who is most likely to experience them?

Sociological research is great for answering just these sorts of questions. But in order to answer our questions well, we must take care in designing our research projects. In this chapter, we’ll consider what aspects of a research project should be considered at the beginning, including specifying the goals of the research, the components that are common across most research projects, and a few other considerations.

One of the first things to think about when designing a research project is what you hope to accomplish, in very general terms, by conducting the research. What do you hope to be able to say about your topic? Do you hope to gain a deep understanding of whatever phenomenon it is that you’re studying, or would you rather have a broad, but perhaps less deep, understanding? Do you want your research to be used by policymakers or others to shape social life, or is this project more about exploring your curiosities? Your answers to each of these questions will shape your research design.

Exploration, Description, Explanation

You’ll need to decide in the beginning phases whether your research will be exploratory, descriptive, or explanatory. Each has a different purpose, so how you design your research project will be determined in part by this decision.

Researchers conducting exploratory research Research that aims to satisfy a researcher’s curiosity about a topic or test the feasibility of a more extensive study. are typically at the early stages of examining their topics. These sorts of projects are usually conducted when a researcher wants to test the feasibility of conducting a more extensive study; he or she wants to figure out the lay of the land, with respect to the particular topic. Perhaps very little prior research has been conducted on this subject. If this is the case, a researcher may wish to do some exploratory work to learn what method to use in collecting data, how best to approach research subjects, or even what sorts of questions are reasonable to ask. A researcher wanting to simply satisfy his or her own curiosity about a topic could also conduct exploratory research. In the case of the study of college students’ addictions to their electronic gadgets, a researcher conducting exploratory research on this topic may simply wish to learn more about students’ use of these gadgets. Because these addictions seem to be a relatively new phenomenon, an exploratory study of the topic might make sense as an initial first step toward understanding it.

In my research on child-free adults, I was unsure what the results might be when first embarking on the study. There was very little empirical research on the topic, so the initial goal of the research was simply to get a better grasp of what child-free people’s lives are like and how their decision to be child free shapes their relationships and everyday experiences. Conducting exploratory research on the topic was a necessary first step, both to satisfy my curiosity about the subject and to better understand the phenomenon and the research participants in order to design a larger, subsequent study.

Sometimes the goal of research is to describe or define a particular phenomenon. In this case, descriptive research Research that aims to describe or define. would be an appropriate strategy. A descriptive study of college students’ addictions to their electronic gadgets, for example, might aim to describe patterns in how use of gadgets varies by gender or college major or which sorts of gadgets students tend to use most regularly.

Researchers at the Princeton Review conduct descriptive research each year when they set out to provide students and their parents with information about colleges and universities around the United States ( http://www.princetonreview.com ). They describe the social life at a school, the cost of admission, and student-to-faculty ratios (to name just a few of the categories reported). Although students and parents may be able to obtain much of this information on their own, having access to the data gathered by a team of researchers is much more convenient and less time consuming.

Market researchers also rely on descriptive research to tell them what consumers think of their products. In fact, descriptive research has many useful applications, and you probably rely on findings from descriptive research without even being aware that that is what you are doing.

Finally, sociological researchers often aim to explain why particular phenomena work in the way that they do. Research that answers “why” questions is referred to as explanatory research Research that aims to identify causes and effects. . In this case, the researcher is trying to identify the causes and effects of whatever phenomenon he or she is studying. An explanatory study of college students’ addictions to their electronic gadgets might aim to understand why students become addicted. Does it have anything to do with their family histories? With their other extracurricular hobbies and activities? With whom they spend their time? An explanatory study could answer these kinds of questions.

There are numerous examples of explanatory social scientific investigations. For example, in a recent study, Dominique Simons and Sandy Wurtele (2010) Simons, D. A., & Wurtele, S. K. (2010). Relationships between parents’ use of corporal punishment and their children’s endorsement of spanking and hitting other children. Child Abuse & Neglect, 34 , 639–646. sought to discover whether receiving corporal punishment from parents led children to turn to violence in solving their interpersonal conflicts with other children. In their study of 102 families with children between the ages of 3 and 7, the researchers found that experiencing frequent spanking did, in fact, result in children being more likely to accept aggressive problem-solving techniques. Another example of explanatory research can be seen in Robert Faris and Diane Felmlee’s research (2011; American Sociological Association, 2011) Faris, R., & Felmlee, D. (2011). Status struggles: Network centrality and gender segregation in same- and cross-gender aggression. American Sociological Review, 76 , 48–73; the American Sociological Association wrote a press release summarizing findings from the study. You can read it at http://asanet.org/press/Press_Release_Popular_Kids_More_Likely_to_Torment_Peers.cfm . The study has also been covered by several media outlets: Pappas, S. (2011). Popularity increases aggression in kids, study finds. Retrieved from http://www.livescience.com/11737-popularity-increases-aggression-kids-study-finds.html on the connections between popularity and bullying. They found, from their study of 8th, 9th, and 10th graders in 19 North Carolina schools, that as adolescents’ popularity increases, so, too, does their aggression. This pattern was found until adolescents reached the top 2% in the popularity ranks. After that, aggression declines.

Idiographic or Nomothetic?

Once you decide whether you will conduct exploratory, descriptive, or explanatory research, you will need to determine whether you want your research to be idiographic or nomothetic. A decision to conduct idiographic research Exhaustive, detailed descriptions or explanations of a singular or very small number of individuals, phenomena, or groups. means that you will attempt to explain or describe your phenomenon exhaustively. While you might have to sacrifice some breadth of understanding if you opt for an idiographic explanation, you will gain a much deeper, richer understanding of whatever phenomenon or group you are studying than you would if you were to pursue nomothetic research. A decision to conduct nomothetic research General, broad descriptions or explanations of many individuals, phenomena, or groups. , on the other hand, means that you will aim to provide a more general, sweeping explanation or description of your topic. In this case, you sacrifice depth of understanding in favor of breadth of understanding.

Let’s look at some specific examples. As a graduate student, I conducted an in-depth study of breast cancer activism (Blackstone, 2003). Blackstone, A. (2003). Racing for the cure and taking back the night: Constructing gender, politics, and public participation in women’s activist/volunteer work . PhD dissertation, Department of Sociology, University of Minnesota, Minneapolis, MN. To do so, I joined an organization of local activists and participated in just about every aspect of the organization over a period of about 18 months. Perhaps it goes without saying, but over the course of a year and a half of participant observation, I learned quite a bit about this organization and its members. In other words, the study revealed the particular idiosyncrasies of the group, but it did not reveal much about the inner workings of other breast cancer activist organizations. Armed with an in-depth understanding about this single group, the study made a contribution to knowledge about how activists operate. For one thing, the organization I observed happened to be one of the largest and most well known of its type at the time, and many other organizations in the movement looked to this organization for ideas about how to operate. Understanding how this model organization worked was important for future activist efforts in a variety of organizations. Further, the study revealed far more intimate details of the inner workings of an activist organization than had it, say, instead been a survey of the top 50 breast cancer organizations in the United States (though that would have been an interesting study as well).

My collaborative research on workplace sexual harassment (Uggen & Blackstone, 2004), Uggen, C., & Blackstone, A. (2004). Sexual harassment as a gendered expression of power. American Sociological Review, 69 , 64–92. on the other hand, aims to provide more sweeping descriptions and explanations. For this nomothetic research project, we mailed surveys to a large sample of young workers who look very much like their peers in terms of their jobs, social class background, gender, and other categories. Because of these similarities, we have been able to speak generally about what young workers’ experiences with sexual harassment are like. In an idiographic study of the same topic, the research team might follow a few workers around every day for a long period of time or conduct a series of very detailed, and lengthy, interviews with 10 or 15 workers.

Applied or Basic?

Finally, you will need to decide what sort of contribution you hope to make with your research. Do you want others to be able to use your research to shape social life? If so, you may wish to conduct a study that policymakers could use to change or create a specific policy. Perhaps, on the other hand, you wish to conduct a study that will contribute to sociological theories or knowledge without having a specific applied use in mind. In the example of the news story on students’ addictions to technological gadgets, an applied study of this topic might aim to understand how to treat such addictions. A basic study of the same topic, on the other hand, might examine existing theories of addiction and consider how this new type of addiction does or does not apply; perhaps your study could suggest ways that such theories may be tweaked to encompass technological addictions.

In Chapter 1 “Introduction” , we learned about both applied and basic research. When designing your research project, think about where you envision your work fitting in on the applied–basic continuum. Recognize, however, that even basic research may ultimately be used for some applied purpose. Similarly, your applied research might not turn out to be applicable to the particular real-world social problem you were trying to solve, but it might better our theoretical understanding of some phenomenon. In other words, deciding now whether your research will be basic or applied doesn’t mean that will be its sole purpose forever. Basic research may ultimately be applied, and applied research can certainly contribute to general knowledge. Nevertheless, it is important to think in advance about what contribution(s) you hope to make with your research.

Key Takeaways

• Exploratory research is usually conducted when a researcher has just begun an investigation and wishes to understand her or his topic generally.
• Descriptive research is research that aims to describe or define the topic at hand.
• Explanatory research is research that aims to explain why particular phenomena work in the way that they do.
• Idiographic investigations are exhaustive; nomothetic investigations are more general.
• While researchers may start out having some idea about whether they aim to conduct applied or basic research, it is also important to keep in mind that applied research may contribute to basic understandings and that basic research may turn out to have some useful application.
• Describe a scenario in which exploratory research might be the best approach. Similarly, describe a scenario in which descriptive and then explanatory research would be the preferred approach.
• Which are you more drawn to personally, applied or basic research? Why?

5.2 Qualitative or Quantitative? Some Specific Considerations

• Describe the role of causality in quantitative research as compared to qualitative research.
• Identify, define, and describe each of the three main criteria for causality.
• Describe the difference between and provide examples of independent and dependent variables.
• Define units of analysis and units of observation, and describe the two common errors people make when they confuse the two.
• Define hypothesis, be able to state a clear hypothesis, and discuss the respective roles of quantitative and qualitative research when it comes to hypotheses.

In Chapter 1 “Introduction” , we discussed the importance of understanding the differences between qualitative and quantitative research methods. Because this distinction is relevant to how researchers design their projects, we’ll revisit it here.

When designing a research project, how issues of causality are attended to will in part be determined by whether the researcher plans to collect qualitative or quantitative data. Causality The idea that one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief. refers to the idea that one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief. In other words, it is about cause and effect.

In a qualitative study, it is likely that you will aim to acquire an idiographic understanding of the phenomenon that you are investigating. Using our example of students’ addictions to electronic gadgets, a qualitative researcher might aim to understand the multitude of reasons that two roommates exhibit addictive tendencies when it comes to their various electronic devices. The researcher might spend time in the dorm room with them, watching how they use their devices, follow them to class and watch them there, observe them at the cafeteria, and perhaps even observe them during their free time. At the end of this very intensive, and probably exhausting, set of observations, the researcher should be able to identify some of the specific causes of each student’s addiction. Perhaps one of the two roommates is majoring in media studies, and all her classes require her to have familiarity with and to regularly use a variety of electronic gadgets. Perhaps the other roommate has friends or family who live overseas, and she relies on a variety of electronic devices to communicate with them. Perhaps both students have a special interest in playing and listening to music, and their electronic gadgets help facilitate this hobby. Whatever the case, in a qualitative study that seeks idiographic understanding, a researcher would be looking to understand the plethora of reasons (or causes) that account for the behavior he or she is investigating.

In a quantitative study, on the other hand, a researcher is more likely to aim for a nomothetic understanding of the phenomenon that he or she is investigating. In this case, the researcher may be unable to identify the specific idiosyncrasies of individual people’s particular addictions. However, by analyzing data from a much larger and more representative group of students, the researcher will be able to identify the most likely, and more general, factors that account for students’ addictions to electronic gadgets. The researcher might choose to collect survey data from a wide swath of college students from around the country. He might find that students who report addictive tendencies when it comes to their gadgets also tend to be people who can identity which of Steven Seagal’s movies he directed, are more likely to be men, and tend to engage in rude or disrespectful behaviors more often than nonaddicted students. It is possible, then, that these associations can be said to have some causal relationship to electronic gadget addiction. However, items that seem to be related are not necessarily causal. To be considered causally related in a nomothetic study, such as the survey research in this example, there are a few criteria that must be met.

The main criteria for causality have to do with plausibility, temporality, and spuriousness. Plausibility means that in order to make the claim that one event, behavior, or belief causes another, the claim has to make sense. For example, if we attend a series of lectures during which a student’s incessant midclass texting or web surfing gets in the way of our ability to focus on the lecture, we might begin to wonder whether people who have a propensity to be rude are more likely to have a propensity to be addicted to their electronic gadgets (and therefore use them during class). However, the fact that there might be a relationship between general rudeness and gadget addiction does not mean that a student’s rudeness could cause him to be addicted to his gadgets. In other words, just because there might be some correlation A relationship between two variables. between two variables does not mean that a causal relationship between the two is really plausible.

The criterion of temporality In social science, this refers to the rule that a cause must precede an effect in time. means that whatever cause you identify must precede its effect in time. As noted earlier, a survey researcher examining the causes of students’ electronic gadget addictions might find that more men than women exhibit addictive tendencies when it comes to their electronic gadgets. Thus the researcher has found a correlation between gender and addiction. So does this mean that a person’s gadget addiction determines his or her gender? Probably not, not only because this doesn’t make any sense but also because a person’s gender identity is most typically formed long before he or she is likely to own any electronic gadgets. Thus gender precedes electronic gadget ownership (and subsequent addiction) in time.

Finally, a spurious relationship A relationship in which two variables appear to be causal but can in fact be explained by some third variable. is one in which an association between two variables appears to be causal but can in fact be explained by some third variable. In the example of a survey assessing students’ addictions to electronic gadgets, the researcher might have found that those who can identify which of Steven Seagal’s films the actor himself directed also exhibit addiction to their electronic gadgets. In case you’re curious, a visit to the Internet Movie Database will tell you that Seagal directed just one of his films, 1994’s On Deadly Ground : http://www.imdb.com/name/nm0000219 . This relationship is exemplified in Figure 5.5 .

So does knowledge about Seagal’s directorial prowess cause gadget addiction? Probably not. A more likely explanation is that being a man makes a person both more likely to know about Seagal’s films and more likely to be addicted to electronic gadgets. In other words, there is a third variable that explains the relationship between Seagal movie knowledge and electronic gadget addiction. This relationship is exemplified in Figure 5.6 .

Let’s consider a few additional, real-world examples of spuriousness. Did you know, for example, that high rates of ice cream sales have been shown to cause drowning? Of course that’s not really true, but there is a positive relationship between the two. In this case, the third variable that causes both high ice cream sales and increased deaths by drowning is time of year, as the summer season sees increases in both (Babbie, 2010). Babbie, E. (2010). The practice of social research (12th ed.). Belmont, CA: Wadsworth. Here’s another good one: it is true that as the salaries of Presbyterian ministers in Massachusetts rise, so, too, does the price of rum in Havana, Cuba. Well, duh, you might be saying to yourself. Everyone knows how much ministers in Massachusetts love their rum, right? Not so fast. Both salaries and rum prices have increased, true, but so has the price of just about everything else (Huff & Geis, 1993). Huff, D., & Geis, I. (1993). How to lie with statistics . New York, NY: Norton. Finally, research shows that the more firefighters present at a fire, the more damage is done at the scene. What this statement leaves out, of course, is that as the size of a fire increases so, too, does the amount of damage caused as does the number of firefighters called on to help (Frankfort-Nachmias & Leon-Guerro, 2011). Frankfort-Nachmias, C., & Leon-Guerro, A. (2011). Social statistics for a diverse society (6th ed.). Thousand Oaks, CA: Pine Forge Press. In each of these examples, it is the presence of a third variable that explains the apparent relationship between the two original variables.

In sum, the following criteria must be met in order for a correlation to be considered causal:

• The relationship must be plausible.
• The cause must precede the effect in time.
• The relationship must be nonspurious.

What we’ve been talking about here is relationships between variables. When one variable causes another, we have what researchers call independent and dependent variables. In the example where gender was found to be causally linked to electronic gadget addiction, gender would be the independent variable and electronic gadget addiction would be the dependent variable. An independent variable A variable that causes another. is one that causes another. A dependent variable A variable that is caused by another. is one that is caused by another. Dependent variables depend on independent variables.

Relationship strength is another important factor to take into consideration when attempting to make causal claims if your research approach is nomothetic. I’m not talking strength of your friendships or marriage (though of course that sort of strength might affect your likelihood to keep your friends or stay married). In this context, relationship strength refers to statistical significance. The more statistically significant a relationship between two variables is shown to be, the greater confidence we can have in the strength of that relationship. We’ll discuss statistical significance in greater detail in Chapter 7 “Sampling” . For now, keep in mind that for a relationship to be considered causal, it cannot exist simply because of the chance selection of participants in a study.

Some research methods, such as those used in qualitative and idiographic research, are not conducive to making predictions about when events or behaviors will occur. In these cases, what we are instead able to do is gain some understanding of the circumstances under which those causal relationships occur: to understand the how of causality. Qualitative research sometimes relies on quantitative work to point toward a relationship that may be interesting to investigate further. For example, if a quantitative researcher learns that men are statistically more likely than women to become addicted to their electronic gadgets, a qualitative researcher may decide to conduct some in-depth interviews and observations of men and women to learn more about how the different contexts and circumstances of men’s and women’s lives might shape their respective chances of becoming addicted. In other words, the qualitative researcher works to understand the contexts in which various causes and effects occur.

Units of Analysis and Units of Observation

Another point to consider when designing a research project, and which might differ slightly in qualitative and quantitative studies, has to do with units of analysis The entity that a researcher wishes to be able to say something about at the end of his or her study; the main focus of the study. and units of observation The item (or items) that a researcher actually observes, measures, or collects in the course of trying to learn something about his or her unit of analysis. . These two items concern what you, the researcher, actually observe in the course of your data collection and what you hope to be able to say about those observations. A unit of analysis is the entity that you wish to be able to say something about at the end of your study, probably what you’d consider to be the main focus of your study. A unit of observation is the item (or items) that you actually observe, measure, or collect in the course of trying to learn something about your unit of analysis. In a given study, the unit of observation might be the same as the unit of analysis, but that is not always the case. Further, units of analysis are not required to be the same as units of observation. What is required, however, is for researchers to be clear about how they define their units of analysis and observation, both to themselves and to their audiences.

More specifically, your unit of analysis will be determined by your research question. Your unit of observation, on the other hand, is determined largely by the method of data collection that you use to answer that research question. We’ll take a closer look at methods of data collection in Chapter 8 “Survey Research: A Quantitative Technique” through Chapter 12 “Other Methods of Data Collection and Analysis” . For now, let’s go back to the example we’ve been discussing over the course of this chapter, students’ addictions to electronic gadgets. We’ll consider first how different kinds of research questions about this topic will yield different units of analysis. Then we’ll think about how those questions might be answered and with what kinds of data. This leads us to a variety of units of observation.

If we were to ask, “Which students are most likely to be addicted to their electronic gadgets?” our unit of analysis would be the individual. We might mail a survey to students on campus, and our aim would be to classify individuals according to their membership in certain social classes in order to see how membership in those classes correlated with gadget addiction. For example, we might find that majors in new media, men, and students with high socioeconomic status are all more likely than other students to become addicted to their electronic gadgets. Another possibility would be to ask, “How do students’ gadget addictions differ, and how are they similar?” In this case, we could conduct observations of addicted students and record when, where, why, and how they use their gadgets. In both cases, one using a survey and the other using observations, data are collected from individual students. Thus the unit of observation in both examples is the individual. But the units of analysis differ in the two studies. In the first one, our aim is to describe the characteristics of individuals. We may then make generalizations about the populations to which these individuals belong, but our unit of analysis is still the individual. In the second study, we will observe individuals in order to describe some social phenomenon, in this case, types of gadget addictions. Thus our unit of analysis would be the social phenomenon.

Another common unit of analysis in sociological inquiry is groups. Groups of course vary in size, and almost no group is too small or too large to be of interest to sociologists. Families, friendship groups, and street gangs make up some of the more common microlevel groups examined by sociologists. Employees in an organization, professionals in a particular domain (e.g., chefs, lawyers, sociologists), and members of clubs (e.g., Girl Scouts, Rotary, Red Hat Society) are all mesolevel groups that sociologists might study. Finally, at the macro level, sociologists sometimes examine citizens of entire nations or residents of different continents or other regions.

A study of student addictions to their electronic gadgets at the group level might consider whether certain types of social clubs have more or fewer gadget-addicted members than other sorts of clubs. Perhaps we would find that clubs that emphasize physical fitness, such as the rugby club and the scuba club, have fewer gadget-addicted members than clubs that emphasize cerebral activity, such as the chess club and the sociology club. Our unit of analysis in this example is groups. If we had instead asked whether people who join cerebral clubs are more likely to be gadget-addicted than those who join social clubs, then our unit of analysis would have been individuals. In either case, however, our unit of observation would be individuals.

Organizations are yet another potential unit of analysis that social scientists might wish to say something about. As you may recall from your introductory sociology class, organizations include entities like corporations, colleges and universities, and even night clubs. At the organization level, a study of students’ electronic gadget addictions might ask, “How do different colleges address the problem of electronic gadget addiction?” In this case, our interest lies not in the experience of individual students but instead in the campus-to-campus differences in confronting gadget addictions. A researcher conducting a study of this type might examine schools’ written policies and procedures, so his unit of observation would be documents. However, because he ultimately wishes to describe differences across campuses, the college would be his unit of analysis.

Of course, it would be silly in a textbook focused on social scientific research to neglect social phenomena as a potential unit of analysis. I mentioned one such example earlier, but let’s look more closely at this sort of unit of analysis. Many sociologists study a variety of social interactions and social problems that fall under this category. Examples include social problems like murder or rape; interactions such as counseling sessions, Facebook chatting, or wrestling; and other social phenomena such as voting and even gadget use or misuse. A researcher interested in students’ electronic gadget addictions could ask, “What are the various types of electronic gadget addictions that exist among students?” Perhaps the researcher will discover that some addictions are primarily centered around social media such as chat rooms, Facebook, or texting while other addictions center on gadgets such as handheld, single-player video games or DVR devices that discourage interaction with others. The resultant typology of gadget addictions would tell us something about the social phenomenon (unit of analysis) being studied. As in several of the preceding examples, however, the unit of observation would likely be individual people.

Finally, a number of social scientists examine policies and principles, the last type of unit of analysis we’ll consider here. Studies that analyze policies and principles typically rely on documents as the unit of observation. Perhaps a researcher has been hired by a college to help it write an effective policy against electronic gadget addiction. In this case, the researcher might gather all previously written policies from campuses all over the country and compare policies at campuses where addiction rates are low to policies at campuses where addiction rates are high.

In sum, there are many potential units of analysis that a sociologist might examine, but some of the most common units include the following:

• Individuals
• Organizations
• Social phenomena
• Policies and principles

Table 5.1 “Units of Analysis and Units of Observation: An Example Using a Hypothetical Study of Students’ Addictions to Electronic Gadgets” includes a summary of the preceding discussion of units of analysis and units of observation.

Table 5.1 Units of Analysis and Units of Observation: An Example Using a Hypothetical Study of Students’ Addictions to Electronic Gadgets

One common error we see people make when it comes to both causality and units of analysis is something called the ecological fallacy Occurs when claims are made about individuals based on group-level data. . This occurs when claims about one lower-level unit of analysis are made based on data from some higher-level unit of analysis. In many cases, this occurs when claims are made about individuals, but only group-level data have been gathered. For example, we might want to understand whether electronic gadget addictions are more common on certain campuses than on others. Perhaps different campuses around the country have provided us with their campus percentage of gadget-addicted students, and we learn from these data that electronic gadget addictions are more common on campuses that have business programs than on campuses without them. We then conclude that business students are more likely than nonbusiness students to become addicted to their electronic gadgets. However, this would be an inappropriate conclusion to draw. Because we only have addiction rates by campus, we can only draw conclusions about campuses, not about the individual students on those campuses. Perhaps the sociology majors on the business campuses are the ones that caused the addiction rates on those campuses to be so high. The point is we simply don’t know because we only have campus-level data. By drawing conclusions about students when our data are about campuses, we run the risk of committing the ecological fallacy.

On the other hand, another mistake to be aware of is reductionism Occurs when claims about groups are made based on individual-level data. . Reductionism occurs when claims about some higher-level unit of analysis are made based on data from some lower-level unit of analysis. In this case, claims about groups or macrolevel phenomena are made based on individual-level data. An example of reductionism can be seen in some descriptions of the civil rights movement. On occasion, people have proclaimed that Rosa Parks started the civil rights movement in the United States by refusing to give up her seat to a white person while on a city bus in Montgomery, Alabama, in December 1955. Although it is true that Parks played an invaluable role in the movement, and that her act of civil disobedience gave others courage to stand up against racist policies, beliefs, and actions, to credit Parks with starting the movement is reductionist. Surely the confluence of many factors, from fights over legalized racial segregation to the Supreme Court’s historic decision to desegregate schools in 1954 to the creation of groups such as the Student Nonviolent Coordinating Committee (to name just a few), contributed to the rise and success of the American civil rights movement. In other words, the movement is attributable to many factors—some social, others political, others economic. Did Parks play a role? Of course she did—and a very important one at that. But did she cause the movement? To say yes would be reductionist.

It would be a mistake to conclude from the preceding discussion that researchers should avoid making any claims whatsoever about data or about relationships between variables. While it is important to be attentive to the possibility for error in causal reasoning about different levels of analysis, this warning should not prevent you from drawing well-reasoned analytic conclusions from your data. The point is to be cautious but not abandon entirely the social scientific quest to understand patterns of behavior.

In some cases, the purpose of research is to test a specific hypothesis or hypotheses. At other times, researchers do not have predictions about what they will find but instead conduct research to answer a question or questions, with an open-minded desire to know about a topic, or to help develop hypotheses for later testing. A hypothesis A statement drawn from theory that posits a researcher’s expectation about the relationship between two or more variables. Hypotheses are often causal though they do not have to be. is a statement, sometimes but not always causal, describing a researcher’s expectation regarding what he or she anticipates finding. Often hypotheses are written to describe the expected relationship between two variables (though this is not a requirement). To develop a hypothesis, one needs to have an understanding of the differences between independent and dependent variables and between units of observation and units of analysis. Hypotheses are typically drawn from theories and usually describe how an independent variable is expected to affect some dependent variable or variables. Researchers following a deductive approach to their research will hypothesize about what they expect to find based on the theory or theories that frame their study. If the theory accurately reflects the phenomenon it is designed to explain, then the researcher’s hypotheses about what he or she will observe in the real world should bear out.

Let’s consider a couple of examples. In my collaborative research on sexual harassment (Uggen & Blackstone, 2004), Uggen, C., & Blackstone, A. (2004). Sexual harassment as a gendered expression of power. American Sociological Review, 69 , 64–92. we once hypothesized, based on feminist theories of sexual harassment, that “more females than males will experience specific sexually harassing behaviors.” What is the causal relationship being predicted here? Which is the independent and which is the dependent variable? In this case, we hypothesized that a person’s sex (independent variable) would predict her or his likelihood to experience sexual harassment (dependent variable).

Sometimes researchers will hypothesize that a relationship will take a specific direction. As a result, an increase or decrease in one area might be said to cause an increase or decrease in another. For example, you might choose to study the relationship between age and legalization of marijuana. Perhaps you’ve done some reading in your crime and deviance class and, based on the theories you’ve read, you hypothesize that “age is negatively related to support for marijuana legalization.” In fact, there are empirical data that support this hypothesis. Gallup has conducted research on this very question since the 1960s. For more on their findings, see Carroll, J. (2005). Who supports marijuana legalization? Retrieved from http://www.gallup.com/poll/19561/who-supports-marijuana-legalization.aspx What have you just hypothesized? You have hypothesized that as people get older, the likelihood of their supporting marijuana legalization decreases. Thus as age (your independent variable) moves in one direction (up), support for marijuana legalization (your dependent variable) moves in another direction (down). If writing hypotheses feels tricky, it is sometimes helpful to draw them out. Figure 5.8 “Hypothesis Describing the Expected Relationship Between Sex and Sexual Harassment” and Figure 5.9 “Hypothesis Describing the Expected Direction of Relationship Between Age and Support for Marijuana Legalization” depict each of the two hypotheses we have just discussed.

Figure 5.8 Hypothesis Describing the Expected Relationship Between Sex and Sexual Harassment

Figure 5.9 Hypothesis Describing the Expected Direction of Relationship Between Age and Support for Marijuana Legalization

Note that you will almost never hear researchers say that they have proven their hypotheses. A statement that bold implies that a relationship has been shown to exist with absolute certainty and that there is no chance that there are conditions under which the hypothesis would not bear out. Instead, researchers tend to say that their hypotheses have been supported (or not). This more cautious way of discussing findings allows for the possibility that new evidence or new ways of examining a relationship will be discovered. Researchers may also discuss a null hypothesis The assumption that no relationship exists between variables in question. , one that predicts no relationship between the variables being studied. If a researcher rejects the null hypothesis, he or she is saying that the variables in question are somehow related to one another.

Quantitative and qualitative researchers tend to take different approaches when it comes to hypotheses. In quantitative research, the goal often is to empirically test hypotheses generated from theory. With a qualitative approach, on the other hand, a researcher may begin with some vague expectations about what he or she will find, but the aim is not to test one’s expectations against some empirical observations. Instead, theory development or construction is the goal. Qualitative researchers may develop theories from which hypotheses can be drawn and quantitative researchers may then test those hypotheses. Both types of research are crucial to understanding our social world, and both play an important role in the matter of hypothesis development and testing.

• In qualitative studies, the goal is generally to understand the multitude of causes that account for the specific instance the researcher is investigating.
• In quantitative studies, the goal may be to understand the more general causes of some phenomenon rather than the idiosyncrasies of one particular instance.
• Quantitative research may point qualitative research toward general causal relationships that are worth investigating in more depth.
• In order for a relationship to be considered causal, it must be plausible and nonspurious, and the cause must precede the effect in time.
• A unit of analysis is the item you wish to be able to say something about at the end of your study while a unit of observation is the item that you actually observe.
• When researchers confuse their units of analysis and observation, they may be prone to committing either the ecological fallacy or reductionism.
• Hypotheses are statements, drawn from theory, which describe a researcher’s expectation about a relationship between two or more variables.
• Qualitative research may point quantitative research toward hypotheses that are worth investigating.
• Do a Google News search for the term ecological fallacy . Chances are good you’ll come across a number of news editorials using this term. Read a few of these editorials or articles, and print one out. Demonstrate your understanding of the term ecological fallacy by writing a short answer discussing whether the author of the article you printed out used the term correctly.
• Pick two variables that are of interest to you (e.g., age and religiosity, gender and college major, geographical location and preferred sports). State a hypothesis that specifies what you expect the relationship between those two variables to be. Now draw your hypothesis, as in Figure 5.5 and Figure 5.6 .

5.3 Triangulation

• Define triangulation.
• Provide an example of triangulation.
• Understand the benefits of triangulation.

Up to this point, we have discussed research design as though it is an either/or proposition. Either you will collect qualitative data or you will collect quantitative data. Either your approach will be idiographic or it will be nomothetic. In truth, you don’t necessarily have to choose one approach over another. In fact, some of the most highly regarded social scientific investigations combine approaches in an effort to gain the most complete understanding of their topic possible. Using a combination of multiple and different research strategies is called triangulation The use of several different research strategies to enhance understanding of a topic. .

Think about the examples we’ve discussed of potential studies of electronic gadget addiction. Now imagine that you could conduct two, or even three, of those studies instead of just one. What if you could conduct a survey of students on campus, a content analysis of campus policies, and observations of students in their natural environments (Brewer & Hunter, 1989; Tashakkori & Teddlie, 1989)? Triangulation isn’t just about using multiple strategies of data collection. Triangulation of measures occurs when researchers use multiple approaches to measure a single variable. Triangulation of theories occurs when researchers rely on multiple theories to help explain a single event or phenomenon. If you’d like to learn more about triangulation, the following sources may be of interest: Brewer, J., & Hunter, A. (1989). Multimethod research: A synthesis of styles . Newbury Park, CA: Sage; Tashakkori, A., & Teddlie, C. (1998). Mixed methodology: Combining qualitative and quantitative approaches . Thousand Oaks, CA: Sage. Aside from being pretty exhausted, and possibly broke, you’d probably end up with a fairly comprehensive understanding of the causes and consequences of, and campus responses to, students’ electronic gadget addictions. And certainly a more comprehensive understanding is better than a less comprehensive one. The drawback, of course, is that you may not have the resources, because of either limited time or limited funding, to conduct such a wide-ranging study.

At this stage, you may be telling yourself (or screaming at me) that it would be nearly impossible to conduct all these studies yourself. You have a life, after all. The good news is that you don’t necessarily have to do everything on your own in order to take advantage of the analytic benefits of triangulation. Perhaps someone already has conducted a large survey of the topic you wish to study. You could find out how those results compare with your one-on-one interviews with people on the same topic. Or perhaps you wish to administer a survey to test the generality of some findings that have been reached through the use of field methods. Whatever the case, don’t forget about all the good research that has come before you that can help strengthen your investigation. Also keep in mind that qualitative and quantitative research methods can be complementary. Triangulation is one way to take advantage of the best in both approaches.

• Triangulation refers to using multiple research strategies in a single research project.
• Triangulation allows researchers to take advantage of the strengths of various methods and at the same time work to overcome some of each method’s weaknesses.
• Select one of the potential research topics you identified while reading Chapter 4 “Beginning a Research Project” . Discuss how you might study the topic if triangulation were your goal.
• Working with the same topic in mind, find two different sociological studies of the same topic. How do the two studies complement each other? Are there ways in which the weaknesses in one study are overcome in the other?

5.4 Components of a Research Project

• Describe useful strategies to employ when searching for literature.
• Describe why sociologists review prior literature and how they organize their literature reviews.
• Identify the main sections contained in scholarly journal articles.
• Identify and describe the major components researchers need to plan for when designing a research project.

In this section, we’ll examine the most typical components that make up a research project, bringing in a few additional components to those we have already discussed. Keep in mind that our purpose at this stage is simply to provide a general overview of research design. The specifics of each of the following components will vary from project to project. Further, the stage of a project at which each of these components comes into play may vary. In later chapters, we will consider more specifically how these components work differently depending on the research method being employed.

Searching for Literature

Familiarizing yourself with research that has already been conducted on your topic is one of the first stages of conducting a research project and is crucial for coming up with a good research design. But where to start? How to start? In Chapter 4 “Beginning a Research Project” , you learned about some of the most common databases that house information about published sociological research. As you search for literature, you may have to be fairly broad in your search for articles.

I’m guessing you may feel you’ve heard enough about electronic gadget addiction in this chapter, so let’s consider a different example here. On my campus, much to the chagrin of a group of student smokers, smoking was recently banned. These students were so upset by the idea that they would no longer be allowed to smoke on university grounds that they staged several smoke-outs during which they gathered in populated areas around campus and enjoyed a puff or two together.

A student in my research methods class wanted to understand what motivated this group of students to engage in activism centered around what she perceived to be, in this age of smoke-free facilities, a relatively deviant act. Were the protesters otherwise politically active? How much effort and coordination had it taken to organize the smoke-outs? The student researcher began her research by attempting to familiarize herself with the literature on her topic. Yet her search in Sociological Abstracts for “college student activist smoke-outs,” yielded no results. Concluding there was no prior research on her topic, she informed me that she would need an alternative assignment to the annotated bibliography A list of sources relevant to a person’s research project. The list is usually presented in alphabetical order, using the citation format of the researcher’s profession. It includes a brief summary of each source’s point of focus, theoretical argument, and major findings underneath each citation. Some annotated bibliographies also contain a brief critique or evaluation of each source. I required since there was no literature for her to review. How do you suppose I responded to this news? What went wrong with this student’s search for literature?

In her first attempt, the student had been too narrow in her search for articles. But did that mean she was off the hook for completing the annotated bibliography assignment? Absolutely not. Instead, she went back to Sociological Abstracts and searched again using different combinations of search terms. Rather than searching for “college student activist smoke-outs” she tried, among other sets of terms, “college student activism.” This time her search yielded a great many articles. Of course, they were not focused on prosmoking activist efforts, but they were focused on her population of interest, college students, and on her broad topic of interest, activism. I suggested that reading articles on college student activism might give her some idea about what other researchers have found in terms of what motivates college students to become involved in activist efforts. I also suggested she could play around with her search terms and look for research on activism centered on other sorts of activities that are perceived by some as deviant, such as marijuana use or veganism. In other words, she needed to be broader in her search for articles.

While this student found success by broadening her search for articles, her reading of those articles needed to be narrower than her search. Once she identified a set of articles to review by searching broadly, it was time to remind herself of her specific research focus: college student activist smoke-outs. Keeping in mind her particular research interest while reviewing the literature gave her the chance to think about how the theories and findings covered in prior studies might or might not apply to her particular point of focus. For example, theories on what motivates activists to get involved might tell her something about the likely reasons the students she planned to study got involved. At the same time, those theories might not cover all the particulars of student participation in smoke-outs. Thinking about the different theories then gave the student the opportunity to focus her research plans and even to develop a few hypotheses about what she thought she was likely to find.

Reviewing the Literature

Developing an annotated bibliography is often one of the early steps that researchers take as they begin to familiarize themselves with prior research on their topic. A second step involves a literature review in which a researcher positions his or her work within the context of prior scholarly work in the area. A literature review addresses the following matters: What sorts of questions have other scholars asked about this topic? What do we already know about this topic? What questions remain? As the researcher answers these questions, he or she synthesizes what is contained in the literature, possibly organizing prior findings around themes that are relevant to his or her particular research focus.

I once advised an undergraduate student who conducted a research project on speciesism, the belief that some species are superior to or have more value and rights than others. Her research question was “Why and how do humans construct divisions between themselves and animals?” This student organized her review of literature around the two parts of her research question: the why and the how. In the “why” section of her literature review, she described prior research that addressed questions of why humans are sometimes speciesist. She organized subsections around the three most common answers that were presented in the scholarly literature. She used the same structure in the “how” section of her literature review, arranging subsections around the answers posed in previous literature about how humans construct divisions between themselves and animals. This organizational scheme helped readers understand what we already know about the topic and what theories we rely on to help make sense of the topic. In addition, by also highlighting what we still don’t know, it helped the student set the stage for her own empirical research on the topic.

The preceding discussion about how to organize a review of scholarly literature assumes that we all know how to read scholarly literature. Yes, yes, I understand that you must know how to read. But reading scholarly articles can be a bit more challenging than reading a textbook. Here are a few pointers about how to do it successfully. First, it is important to understand the various sections that are typically contained in scholarly journals’ reports of empirical research. One of the most important and easiest to spot sections of a journal article is its abstract A short paragraph at the beginning of a journal article that summarizes the author’s research question(s), research method(s), and key findings. , the short paragraph at the beginning of an article that summarizes the author’s research question, methods used to answer the question, and key findings. The abstract may also give you some idea about the theoretical proclivities of the author. As a result, reading the abstract gives you both a framework for understanding the rest of the article and the punch line. It tells you what the author(s) found and whether the article is relevant to your area of inquiry.

After the abstract, most journal articles will contain the following sections (although exact section names are likely to vary): introduction, literature review, methodology, findings, and discussion. Of course, there will also be a list of references cited, Lists of references cited are a useful source for finding additional literature in an area. and there may be a few tables, figures, or appendices at the end of the article as well. While you should get into the habit of familiarizing yourself with articles you wish to cite in their entirety , there are strategic ways to read journal articles that can make them a little easier to digest. Once you have read the abstract and determined that this is an article you’d like to read in full, read through the discussion section at the end of the article next. Because your own review of literature is likely to emphasize findings from previous literature, you should make sure that you have a clear idea about what those findings are. Reading an article’s discussion section helps you understand what the author views as the study’s major findings and how the author perceives those findings to relate to other research.

As you read through the rest of the article, think about the elements of research design that we have covered in this chapter. What approach does the researcher take? Is the research exploratory, descriptive, or explanatory? Is it inductive or deductive? Idiographic or nomothetic? Qualitative or quantitative? What claims does the author make about causality? What are the author’s units of analysis and observation? Use what you have learned in this chapter about the promise and potential pitfalls associated with each of these research elements to help you responsibly read and understand the articles you review. Future chapters of this text will address other elements of journal articles, including choices about measurement, sampling, and research method. As you learn about these additional items, you will increasingly gain more knowledge that you can apply as you read and critique the scholarly literature in your area of inquiry.

Additional Important Components

Thinking about the overarching goals of your research project and finding and reviewing the existing literature on your topic are two of the initial steps you’ll take when designing a research project. Forming a clear research question, as discussed in Chapter 4 “Beginning a Research Project” , is another crucial step. There are a number of other important research design components you’ll need to consider, and we will discuss those here.

At the same time that you work to identify a clear research question, you will probably also think about the overarching goals of your research project. Will it be exploratory, descriptive, or explanatory? Will your approach be idiographic or nomothetic, inductive or deductive? How you design your project might also be determined in part by whether you aim for your research to have some direct application or if your goal is to contribute more generally to sociological knowledge about your topic. Next, think about what your units of analysis and units of observation will be. These will help you identify the key concepts you will study. Once you have identified those concepts, you’ll need to decide how to define them, and how you’ll know that you’re observing them when it comes time to collect your data. Defining your concepts, and knowing them when you see them, has to do with conceptualization and operationalization, the focus of Chapter 6 “Defining and Measuring Concepts” . Of course, you also need to know what approach you will take to collect your data. Thus identifying your research method is another important part of research design. You also need to think about who your research participants will be and what larger group(s) they may represent. These topics will be the focus of Chapter 7 “Sampling” . Last, but certainly not least, you should consider any potential ethical concerns that could arise during the course of your research project. These concerns might come up during your data collection, but they might also arise when you get to the point of analyzing or sharing your research results.

Decisions about the various research components do not necessarily occur in sequential order. In fact, you may have to think about potential ethical concerns even before zeroing in on a specific research question. Similarly, the goal of being able to make generalizations about your population of interest could shape the decisions you make about your method of data collection. Putting it all together, the following list shows some of the major components you’ll need to consider as you design your research project:

• Research question
• Literature review
• Research strategy (idiographic or nomothetic, inductive or deductive)
• Research goals (basic or applied)
• Units of analysis and units of observation
• Key concepts (conceptualization and operationalization)
• Method of data collection
• Research participants (sample and population)
• Ethical concerns
• When identifying and reading relevant literature, be broad in your search for articles, but be narrower in your reading of articles.
• Writing an annotated bibliography can be a helpful first step to familiarize yourself with prior research in your area of interest.
• Literature reviews summarize and synthesize prior research.
• Literature reviews are typically organized around substantive ideas that are relevant to one’s research question rather than around individual studies or article authors.
• When designing a research project, be sure to think about, plan for, and identify a research question, a review of literature, a research strategy, research goals, units of analysis and units of observation, key concepts, method(s) of data collection, population and sample, and potential ethical concerns.
• Find and read a complete journal article that addresses a topic that is of interest to you (perhaps using Sociological Abstracts, which is introduced in Chapter 4 “Beginning a Research Project” ). In four to eight sentences, summarize the author’s research question, theoretical framing, methods used, and major findings. Reread the article, and see how close you were in reporting these key elements. What did you understand and remember best? What did you leave out? What reading strategies may have helped you better recall relevant details from the article?
• Using the example of students’ electronic gadget addictions, design a hypothetical research project by identifying a plan for each of the nine components of research design that are presented in this section.
• Principles of Sociological Inquiry: Qualitative and Quantitative Methods. Provided by : Saylor Academy. Located at : https://saylordotorg.github.io/text_principles-of-sociological-inquiry-qualitative-and-quantitative-methods/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

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Introduction to Descriptive Design Research 

• Author Survey Point Team
• Published September 4, 2023

Descriptive design research explains phenomena, populations, or situations through patterns of behavior. This is done through the collection of data via observation, surveys, interviews, and experiments. Descriptive design research answers questions about what is happening and why.  

In-depth research is conducted with the intent of learning as much as possible about a subject. Widely seen in the fields of social sciences and health sciences. Now seen in other areas such as business, education, and economics.  

According to Creswell , the descriptive research design is a study that describes the characteristics of a population or phenomenon being studied. Primarily used to gain an understanding of a group or phenomenon. This involves collecting data through surveys, interviews, or observation. Descriptive research designs answer “Who, What, When, Where, Why, and How.” 

Table of Contents

Characteristics of Descriptive Design Research  

The descriptive design research would entail the following characteristics:  

• Usability:  The usability is by observing and describing the behavior of the subject. This is without influencing it in any way. 
• Non-Experimental:  This research is non-experimental in nature. It does not involve any manipulation of variables. 
• Process:  There is a collection of large amounts of data. These can be through interviews, observations, surveys, and/or questionnaires, and other sources. 
• Analysis:  Seeks to describe, analyze, and explain phenomena in detail. 
• Requirement:  This includes answering questions related to the characteristics of a population/phenomenon. 
• Control:  is usually used when a researcher has limited control over the variables of interest and can only observe them. 
• Aim:  is used to gain a better understanding of a phenomenon and to form hypotheses for further investigation. 

Descriptive Design Research Examples  

Let’s take an example where researchers use descriptive design research:  

Suppose a researcher surveys a sample of college students to know what influences their decision to attend college. The researcher would ask questions such as:  

Q. What led you to decide to attend college?  

Q. How supportive were your family and friends of your decision?  

Q. What do you aim to get out of college?  

The researcher would then analyze the responses. In an effort to learn what makes some pupils more likely to go to college than others, we conducted a survey. 

On the whole, a researcher can use descriptive design research, include: 

• A study that describes the prevalence of anxiety among college students. 
• A survey that describes the attitudes of employees towards their workplace. 
• An observational study that describes the behavior of customers in a retail store. 
• A cross-sectional study that describes the health behaviors of a particular population. 
• A longitudinal study that describes changes in cognitive function among older adults. 

Types of Descriptive Design Research Surveys   

Descriptive design research classifies into the following types: 

Census Survey    

A census survey collects data from every member of a population. In this research method, the researchers account for the whole population of a specific area. After which, they analyze age, gender, income, occupation, and other demographic information. 

Sample Survey   

A sample survey gathers data on a selected population. In effect, this is to gain a better understanding of its characteristics through questions. In this case, questions explore characteristics of the population like demographics, behaviors, attitudes, beliefs, etc.  

Comparative Survey  

A comparative survey involves the comparison of two or more entities. Therefore, this type of research identifies the similarities and differences between the entities. On the whole, to gain further insights into their respective characteristics.  

Comparative surveys explore topics such as customer satisfaction, product preferences, and employee attitudes. 

Longitudinal Survey   

A longitudinal survey is a collection of repeated observations on the same subjects. It identifies changes over a period of time. This survey explores the relationships between variables. These surveys often study the effects of aging, career development, and health outcomes. 

Cross-Sectional Survey   

In this research method, a sample from a population is taken and studied by the researchers at one specific time. It can be either single-variable or multivariable research .  

Cross-sectional surveys collect the population’s attitudes, beliefs, and behaviors at a particular time. 

When is it best to conduct a descriptive survey? 

Below is an example of a market research goal that can be met using a descriptive survey design. Survey research design provides researchers with the data they need to make educated judgments that will ultimately benefit the development of their organization. 

Define a distinct client type profile with the use of a descriptive survey design. For instance, a cosmetics business can use a descriptive survey to categorize customers into groups based on their characteristics. 

In order to learn how consumers feel about a given brand or product, one must: 

• Customers’ opinions on the unique selling proposition (USP) of your products and services can be gleaned through the usage of this research methodology . 
• You can conduct market research by asking customers what they like and don’t like about your product’s design, color scheme, packaging, etc. 
• A descriptive survey design can help you figure out what kind of customer acts in a certain way so you can better understand their motivations and preferences. For instance, a health drink manufacturer would inquire how many of their consumers also buy tea. Customers can be categorized in this way for more precise marketing. 
• Customers can shed light on shopping behaviors and the factors that influence purchases, which can be used to make educated predictions. 
• Customers are more likely to make purchases in November and December, according to surveys, because of the holidays and the approaching new year.  
• Companies can utilize the results of these surveys to anticipate sales and prepare for an influx of clients. 

Steps to Conduct Descriptive Design Research  

To list the steps involved in conducting descriptive design research: 

• Identify the question:  it is essential to identify the research problem or question. This is so that the researchers have clarity about the goal of the study.  
• Develop a research design:  The next step is to develop a research design. You should determine the data type you will collect and the methods you will use to analyze the data. 
• Collect the data:  Data collection methods include surveys, interviews, observations, or other methods. 
• Analyze the data:  The data analysis includes summarizing the data. For this, creating graphs or charts to visualize the data is mandatory. 
• Interpret the results:  The final step is to interpret the results of the study. That involves summarizing the findings and discussing the implications of the results. 

Advantages of Descriptive Design Research 

Descriptive design research has several advantages, including: 

• Provides a detailed and accurate description of a particular phenomenon or situation. 
• Generates hypotheses for future research. 
• Identify patterns or trends in the data. 

Limitations of Descriptive Design Research 

Descriptive design research also has some limitations, including: 

• Limited in its ability to identify causal relationships between variables. 
• It may not provide insight into why a particular phenomenon is occurring. 
• It may not be generalizable to other populations or situations. 

Conclusion  

In conclusion, descriptive design is an efficient method for performing research. It explores relationships between variables and draws meaningful conclusions from the data collected. The descriptive design provides an in-depth understanding of the hypothesis. This helps researchers get conclusive findings and make informed decisions.  

Descriptive design research is a valuable method because it analyzes a particular situation. Not to mention, it provides an accurate description of a particular population, behavior, or condition. Despite its drawbacks, this approach is a powerful means of discovering trends and gaining understanding. 

Is descriptive design research the same as qualitative research?  

No, descriptive design research is not the same as qualitative research. It can involve qualitative methods of collecting data, such as interviews or focus groups. In this case, descriptive design research also has quantitative methods, such as surveys or observational studies. 

How is descriptive design research different from experimental research?  

Descriptive design research focuses on analyzing a particular phenomenon or situation. Another key point, it focuses on identifying causal relationships between variables. 

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Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

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This paper is in the following e-collection/theme issue:

Published on 16.4.2024 in Vol 26 (2024)

User-Centered Development of a Patient Decision Aid for Choice of Early Abortion Method: Multi-Cycle Mixed Methods Study

Authors of this article:

Original Paper

• Kate J Wahl 1 , MSc   ; 
• Melissa Brooks 2 , MD   ; 
• Logan Trenaman 3 , PhD   ; 
• Kirsten Desjardins-Lorimer 4 , MD   ; 
• Carolyn M Bell 4 , MD   ; 
• Nazgul Chokmorova 4 , MD   ; 
• Romy Segall 2 , BSc, MD   ; 
• Janelle Syring 4 , MD   ; 
• Aleyah Williams 1 , MPH   ; 
• Linda C Li 5 , PhD   ; 
• Wendy V Norman 4, 6 * , MD, MHSc   ; 
• Sarah Munro 1, 3 * , PhD  

1 Department of Obstetrics and Gynecology, University of British Columbia, Vancouver, BC, Canada

2 Department of Obstetrics and Gynecology, Dalhousie University, Halifax, NS, Canada

3 Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA, United States

4 Department of Family Practice, University of British Columbia, Vancouver, BC, Canada

5 Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada

6 Department of Public Health, Environments and Society, Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom

*these authors contributed equally

Corresponding Author:

Kate J Wahl, MSc

Department of Obstetrics and Gynecology

University of British Columbia

4500 Oak Street

Vancouver, BC, V6H 3N1

Phone: 1 4165231923

Email: [email protected]

Background: People seeking abortion in early pregnancy have the choice between medication and procedural options for care. The choice is preference-sensitive—there is no clinically superior option and the choice depends on what matters most to the individual patient. Patient decision aids (PtDAs) are shared decision-making tools that support people in making informed, values-aligned health care choices.

Objective: We aimed to develop and evaluate the usability of a web-based PtDA for the Canadian context, where abortion care is publicly funded and available without legal restriction.

Methods: We used a systematic, user-centered design approach guided by principles of integrated knowledge translation. We first developed a prototype using available evidence for abortion seekers’ decisional needs and the risks, benefits, and consequences of each option. We then refined the prototype through think-aloud interviews with participants at risk of unintended pregnancy (“patient” participants). Interviews were audio-recorded and documented through field notes. Finally, we conducted a web-based survey of patients and health care professionals involved with abortion care, which included the System Usability Scale. We used content analysis to identify usability issues described in the field notes and open-ended survey questions, and descriptive statistics to summarize participant characteristics and close-ended survey responses.

Results: A total of 61 individuals participated in this study. Further, 11 patients participated in think-aloud interviews. Overall, the response to the PtDA was positive; however, the content analysis identified issues related to the design, language, and information about the process and experience of obtaining abortion care. In response, we adapted the PtDA into an interactive website and revised it to include consistent and plain language, additional information (eg, pain experience narratives), and links to additional resources on how to find an abortion health care professional. In total, 25 patients and 25 health care professionals completed the survey. The mean System Usability Scale score met the threshold for good usability among both patient and health care professional participants. Most participants felt that the PtDA was user-friendly (patients: n=25, 100%; health care professionals: n=22, 88%), was not missing information (patients: n=21, 84%; health care professionals: n=18, 72%), and that it was appropriate for patients to complete the PtDA before a consultation (patients: n=23, 92%; health care professionals: n=23, 92%). Open-ended responses focused on improving usability by reducing the length of the PtDA and making the website more mobile-friendly.

Conclusions: We systematically designed the PtDA to address an unmet need to support informed, values-aligned decision-making about the method of abortion. The design process responded to a need identified by potential users and addressed unique sensitivities related to reproductive health decision-making.

Introduction

In total, 1 in 3 pregnancy-capable people in Canada will have an abortion in their lifetimes, and most will seek care early in pregnancy [ 1 ]. Medication abortion (using the gold-standard mifepristone/misoprostol regimen) and procedural abortion are common, safe, and effective options for abortion care in the first trimester [ 2 , 3 ]. The choice between using medications and presenting to a facility for a procedure is a preference-sensitive decision; there is no clinically superior option and the choice depends on what matters most to the individual patient regarding the respective treatments and the features of those options [ 4 - 6 ].

The choice of method of abortion can involve a process of shared decision-making, in which the patient and health care professional share the best available evidence about options, and the patient is supported to consider those options and clarify an informed preference [ 7 ]. There are many types of interventions available to support shared decision-making, including interventions targeting health care professionals (eg, educational materials, meetings, outreach visits, audit and feedback, and reminders) and patients (eg, patient decision aids [PtDA], appointment preparation packages, empowerment sessions, printed materials, and shared decision-making education) [ 8 ]. Of these interventions, PtDAs are well-suited to address challenges to shared decision-making about the method of abortion, including limited patient knowledge, public misinformation about options, poor access to health care professionals with sufficient expertise, and apprehension about abortion counseling [ 9 ].

PtDAs are widely used interventions that support people in making informed, deliberate health care choices by explicitly describing the health problem and decision, providing information about each option, and clarifying patient values [ 10 ]. The results of the 2023 Cochrane systematic review of 209 randomized controlled trials indicate that, compared to usual care (eg, information pamphlets or webpages), the use of PtDAs results in increases in patient knowledge, expectations of benefits and harms, clarity about what matters most to them, and participation in making a decision [ 11 ]. Of the studies included in the systematic review, 1 tested the effect of a PtDA leaflet for method of abortion and found that patients eligible for both medication and procedural abortion who received the PtDA were more knowledgeable, and had lower risk perceptions and decisional conflict than those who were in the control group [ 12 ]. However, that PtDA was developed 20 years ago in the UK health system and was not publicly available. A recent environmental scan of PtDAs for a method of abortion found that other available options meet few of the criteria set by the International Patient Decision Aid Standards (IPDAS) collaboration and do not include language and content optimized for end users [ 9 , 13 ].

Consequently, no PtDAs for method of abortion were available in Canada at the time of this study. This was a critical gap for both patients and health care professionals as, in 2017, mifepristone/misoprostol medication abortion came to the market, offering a new method of choice for people seeking abortion in the first trimester [ 14 ]. Unlike most jurisdictions, in Canada medication abortion is typically prescribed in primary care and dispensed in community pharmacies. Offering a PtDA in preparation for a brief primary care consultation allows the person seeking abortion more time to digest new information, consider their preferences, be ready to discuss their options, and make a quality decision.

In this context, we identified a need for a high-quality and publicly available PtDA to support people in making an informed choice about the method of abortion that reflects what is most important to them. Concurrently, our team was working in collaboration with knowledge users (health care professionals, patients, and health system decision makers) who were part of a larger project to investigate the implementation of mifepristone in Canada [ 15 , 16 ]. We, therefore, aimed to develop and evaluate the usability of a web-based PtDA for the Canadian context, where abortion care is publicly funded and available without legal restriction.

Study Design

We performed a mixed methods user-centered development and evaluation study informed by principles of integrated knowledge translation. Integrated knowledge translation is an approach to collaborative research in which researchers and knowledge users work together to identify a problem, conduct research as equal partners to address that problem, and coproduce research products that aim to impact health service delivery [ 17 ]. We selected this approach to increase the likelihood that our end PtDAs would be relevant, useable, and used for patients and health care professionals in Canada [ 17 ]. The need for a PtDA was identified through engagement with health care professionals. In 2017, they highlighted the need for patients to be supported in choosing between procedural care—which historically represented more than 90% of abortions in Canada [ 18 ]—and the newly available medication option [ 19 , 20 ]. This need was reaffirmed in 2022 by the Canadian federal health agency, Health Canada, which circulated a request for proposals to generate “evidence-based, culturally-relevant information aimed at supporting people in their reproductive decision-making and in accessing abortion services as needed” [ 21 ].

We operationalized integrated knowledge translation principles in a user-centered design process. User-centered design “grounds the characteristics of an innovation in information about the individuals who use that innovation, with a goal of maximizing ‘usability in context’” [ 22 ]. In PtDA development, user-centered design involves iteratively understanding users, developing and refining a prototype, and observing user interaction with the prototype [ 23 , 24 ]. Like integrated knowledge translation, this approach is predicated on the assumption that involving users throughout the process increases the relevance of the PtDA and the likelihood of successful implementation [ 24 ].

Our design process included the following steps ( Figure 1 ): identification of evidence about abortion patients’ decisional needs and the attributes of medication and procedural abortion that matter most from a patient perspective; development of a paper-based prototype; usability testing via think-aloud interviews with potential end users; refinement of the PtDA prototype into an interactive website; usability testing via a survey with potential end users and abortion health care professionals; and final revisions before launching the PtDA for real-world testing. Our systematic process was informed by user-centered methods for PtDA development [ 23 , 24 ], guidance from the IPDAS collaboration [ 25 - 27 ], and the Standards for Universal Reporting of Patient Decision Aid Evaluation checklist [ 10 ].

Our multidisciplinary team included experts in shared decision-making (SM and LT), a PhD student in patient-oriented knowledge translation (KJW), experts in integrated knowledge translation with health care professionals and policy makers (WVN and SM), clinical experts in abortion counseling and care (WVN and MB), a medical undergraduate student (RS), a research project coordinator (AW), and family medicine residents (KD-L, CMB, NC, and JS) who had an interest in abortion care. Additionally, a panel of experts external to the development process reviewed the PtDA for clinical accuracy following each revision of the prototype. These experts included coauthors of the national Society for Obstetricians and Gynaecologists of Canada (SOGC) clinical practice guidelines for abortion care in Canada. They were invited to this project because of their knowledge of first-trimester abortion care as well as their ability to support the implementation of the PtDA in guidelines and routine clinical practice.

Ethical Considerations

The research was approved by the University of British Columbia Children’s and Women’s Research Ethics Board (H16-01006) and the Nova Scotia Health Research Ethics Board (1027637). In each round of testing, participants received a CAD $20 (US $14.75) Amazon gift card by email for their participation.

Preliminary Work: Identification of Evidence

We identified the decisional needs of people seeking early abortion care using a 2018 systematic review of reasons for choosing an abortion method [ 28 ], an additional search that identified 1 study conducted in Canada following the 2017 availability of mifepristone/misoprostol medication abortion [ 29 ], and the SOGC clinical practice guidelines [ 2 , 3 ]. The review identified several key factors that matter most for patient choice of early abortion method: perceived simplicity and “naturalness,” fear of complication or bleeding , fear of anesthesia or surgery , timing of the procedure , and chance of sedation . The additional Canadian study found that the time required to complete the abortion and side effects were important factors. According to the SOGC clinical practice guidelines, the key information that should be communicated to the patient are gestational age limits and the risk of complications with increasing gestational age [ 2 , 3 ]. The guidelines also indicate that wait times , travel times , and cost considerations may be important in a person’s choice of abortion method and should be addressed [ 2 , 3 ].

We compiled a long list of attributes for our expert panel and then consolidated and refined the attribute list through each stage of the prototype evaluation. For evidence of how these factors differed for medication and procedural abortion, we drew primarily from the SOGC clinical practice guidelines for abortion [ 2 , 3 ]. For cost considerations, we described the range of federal, provincial, and population-specific programs that provide free coverage of abortion care for people in Canada.

Step 1: Developing the Prototype

Our goal was to produce an interactive, web-based PtDA that would be widely accessible to people seeking an abortion in Canada by leveraging the widespread use of digital health information, especially among reproductive-aged people [ 30 ]. Our first prototype was based on a previously identified paper-based question-and-answer comparison grid that presented evidence-based information about the medication and procedural options [ 9 , 31 ]. We calculated readability by inputting the plain text of the paper-based prototype into a Simple Measure of Gobbledygook (SMOG) Index calculator [ 32 ].

We made 2 intentional deviations from common practices in PtDA development [ 33 ]. First, we did not include an “opt-out” or “do nothing” option, which would describe the natural course of pregnancy. We chose to exclude this option to ensure clarity for users regarding the decision point; specifically, our decision point of interest was the method of abortion, not the choice to terminate or continue a pregnancy. Second, we characterized attributes of the options as key points rather than positive and negative features to avoid imposing value judgments onto subjective features (eg, having the abortion take place at home may be beneficial for some people but may be a deterrent for others).

Step 2: Usability Testing of the Prototype

We first conducted usability testing involving think-aloud interviews with patient participants to assess the paper-based prototype. Inclusion criteria included people aged 18-49 years assigned-female-at-birth who resided in Canada and could speak and read English. In January 2020, we recruited participants for the first round of think-aloud interviews [ 34 ] via email and poster advertising circulated to (1) a network of parent research advisors who were convened to guide a broader program of research about pregnancy and childbirth in British Columbia, Canada, and (2) a clinic providing surgical abortion care in Nova Scotia, Canada, as well as snowball sampling with participants. We purposively sought to advertise this study with these populations to ensure variation in age, ethnicity, level of education, parity, and abortion experience. Interested individuals reviewed this study information form and provided consent to participate, before scheduling an interview. The interviewer asked participants to think aloud as they navigated the prototype, for example describing what they liked or disliked, missing information, or lack of clarity. The interviewer noted the participant’s feedback on a copy of the prototype during the interview. Finally, the participant responded to questions adapted from the System Usability Scale [ 35 ], a measure designed to collect subjective ratings of a product’s usability, and completed a brief demographic questionnaire. The interviews were conducted via videoconferencing and were audio recorded. We deidentified the qualitative data and assigned each participant a unique identifier. Then, the interviewer listened to the recording and revised their field notes with additional information including relevant quotes.

For the analysis of think-aloud interviews, we used inductive content analysis to describe the usability and acceptability of different elements of the PtDA [ 36 ]. Further, 3 family medicine residents (KD-L, CMB, and NC) under guidance from a senior coauthor (SM) completed open coding to develop a list of initial categories, which we grouped under higher-order headings. We then organized these results in a table to illustrate usability issues (categories), illustrative participant quotes, and modifications to make. We then used the results of interviews to adapt the prototype into a web-based format, which we tested via further think-aloud interviews and a survey with people capable of becoming pregnant and health care professionals involved with abortion care.

Step 3: Usability Testing of the Website

For the web-based format, we used DecideApp PtDA open-source software, which provides a sustainable solution to the problems of low quality and high maintenance costs faced by web-based PtDAs by allowing developers to host, maintain, and update their tools at no cost. This software has been user-tested and can be accessed by phone, tablet, or computer [ 37 , 38 ]. It organizes a PtDA into 6 sections: Introduction, About Me, My Values, My Choice, Review, and Next Steps. In the My Values section, an interactive values clarification exercise allows users to rank and make trade-offs between attributes of the options. The final pages provide an opportunity for users to make a choice, complete a knowledge self-assessment, and consider the next steps to access their chosen method.

From July to August 2020, we recruited patient and health care professional participants using Twitter and the email list of the Canadian Abortion Providers Support platform, respectively. Participants received an email with a link to the PtDA and were redirected to the survey once they had navigated through the PtDA. As above, inclusion criteria included people aged 18-49 years assigned as female-at-birth who resided in Canada. Among health care professionals, we included eligible prescribers who may not have previously engaged in abortion care (family physicians, residents, nurse practitioners, and midwives), and allied health professionals and stakeholders who provide or support abortion care, who practiced in Canada. All participants had to speak and read English.

The survey included 3 sections: usability, implementation, and participant characteristics. The usability section consisted of the System Usability Scale [ 35 ], and purpose-built questions about what participants liked and disliked about the PtDA. The implementation section included open- and close-ended questions about how the PtDA compares to other resources and when it could be implemented in the care pathway. Patient participants also completed the Control Preference Scale, a validated measure used to determine their preferred role in decision-making (active, collaborative, or passive) [ 39 ]. Data on participant characteristics included gender, abortion experience (patient participants), and abortion practice (health care professional participants). We deidentified the qualitative data and assigned each participant a unique identifier. For the analysis of survey data, we characterized close-ended responses using descriptive statistics, and, following the analysis procedures described in Step 2 in the Methods section, used inductive content analysis of open-ended responses to generate categories associated with usability and implementation [ 36 ]. In 2021, we made minor revisions to the website based on the results of usability testing and published the PtDA for use in routine clinical care.

In the following sections, we outline the results of the development process including the results of the think-aloud interviews and survey, as well as the final decision aid prototype.

Our initial prototype, a paper-based question-and-answer comparison grid, presented evidence-based information comparing medication and procedural abortion. The first version of the prototype also included a second medication abortion regimen involving off-label use of methotrexate, however, we removed this option following a review by the clinical expert panel who advised us that there is very infrequent use of this regimen in Canada in comparison to the gold standard medication abortion option, mifepristone. Other changes at this stage involved clarifying the scope of practice (health care professionals other than gynecologists can perform a procedural abortion), abortion practice (gestational age limit and how the medication is taken), the abortion experience (what to expect in terms of bleeding), and risk (removing information about second- and third-trimester abortion). The updated prototype was finalized by a scientist (SM) and trainee (KJW) with expertise in PtDA development. The prototype (see Multimedia Appendix 1 ) was ultimately 4 pages long and described 18 attributes of each option framed as Frequently Asked Questions, including abortion eligibility (How far along in pregnancy can I be?), duration (How long does it take?), and side effects (How much will I bleed?). The SMOG grade level was 8.4.

Participant Characteristics

We included 11 participants in think-aloud interviews between January and July 2020, including 7 recruited through a parent research advisory network and 4 individuals who had recently attended an abortion clinic. The mean interview duration was 36 minutes (SD 6 minutes). The participants ranged in age from 31 to 37 years. All had been pregnant and 8 out of 11 (73%) participants had a personal experience of abortion (4 participants who had recently attended an abortion clinic and 4 participants from the parent research advisory who disclosed their experience during the interview). The characteristics of the sample are reported in Table 1 .

Overall, participants had a positive view of the paper-based, comparison grid PtDA. In total, 1 participant who had recently sought an abortion said, “I think this is great and super helpful. It would’ve been awesome to have had access to this right away … I don’t think there’s really anything missing from here that I was Googling about” (DA010). The only participant who expressed antichoice views indicated that the PtDA would be helpful to someone seeking to terminate a pregnancy (DA001). Another participant said, “[The PtDA] is not biased, it’s not like you’re going to die. It’s a fact, you know the facts and then you decide whether you want it or not. A lot of people feel it’s so shameful and judgmental, but this is very straightforward. I like it.” (DA002). Several participants stated they felt more informed and knowledgeable about the options.

In response to questions adapted from the System Usability Scale, all 11 participants agreed that the PtDA was easy to use, that most people could learn to use it quickly, and that they felt very confident using the prototype, and disagreed that it was awkward to use. In total, 8 (73%) participants agreed with the statement that the components of the PtDA were well-integrated. A majority of participants disagreed with the statements that the website was unnecessarily complex (n=8, 73%), that they would need the support of an expert to use it (n=8, 73%), that it was too inconsistent (n=9, 82%), and that they would need to learn a lot before using it (n=8, 73%). Further, 2 (18%) participants agreed with the statements that the PtDA was unnecessarily complex and that they would need to learn a lot before using it. Furthermore, 1 (9%) participant agreed with the statement that the PtDA was too inconsistent.

Through inductive analysis of think-aloud interviews, we identified 4 key usability categories: design, language, process, and experience.

Participants liked the side-by-side comparison layout, appreciated the summary of key points to remember, and said that overall, the presented information was clear. For example, 1 participant reflected, “I think it’s very clear ... it’s very simplistic, people will understand the left-hand column is for medical abortion and the right-hand column is for surgical.” (DA005) Some participants raised concerns about the aesthetics of the PtDA, difficulties recalling the headers across multiple pages, and the overall length of the PtDA.

Participants sought to clarify language at several points in the PtDA. Common feedback was that the gestational age limit for the medication and the procedure should be clarified. Participants also pointed out inconsistent use of language (eg, doctor and health care professional) and medical jargon.

Several participants were surprised to learn that family doctors could provide abortion care. Others noted that information about the duration—including travel time—and number of appointments for both medication and procedural abortion could be improved. In addition to clarifying the abortion process, several participants suggested including additional information and resources to help identify an abortion health care professional, understand when to seek help for abortion-related complications, and access emotional support. It was also important to participants that financial impacts (eg, hospital parking and menstrual pads) were included for each option.

Participants provided insight into the description of the physical, psychological, and other consequences associated with the abortion medication and procedure. Participants who had both types of abortion care felt that the description of pain that “may be worse than a period” was inaccurate. Other participants indicated that information about perceived and real risks was distressing or felt out of place, such as correcting myths about future fertility or breast cancer. Some participants indicated that patient stories would be valuable saying, for example, “I think what might be nice to help with the decision-making process is reading stories of people’s experiences” (DA006).

Modifications Made

Changes made based on these findings are described in Table 2 . Key user-centered modifications included transitioning to a web-based format with a consistent color scheme, clarifying who the PtDA is for (for typical pregnancies up to 10 weeks), adding information about telemedicine to reflect guidelines for the provision of abortion during pandemics, and developing brief first-person qualitative descriptions of the pain intensity for each option.

Through analysis of the interviews and consultation with our panel of clinical experts, we also identified that, among the 18 initial attributes in our prototype, 7 had the most relative importance to patients in choosing between medication and procedural abortion. These attributes also represented important differences between each option which forced participants to consider the trade-offs they were willing to make. Thus we moved all other potential attributes into an information section (My Options) that supported the user to gain knowledge before clarifying what mattered most to them by considering the differences between options (My Values).

a PtDA: patient decision aid.

b SOGC: Society of Obstetricians and Gynaecologists of Canada.

Description of the PtDA

As shown in Figure 2 , the revised version of the PtDA resulting from our systematic process is an interactive website. Initially, the title was My Body, My Choice ; however, this was changed to avoid association with antivaccine campaigns that co-opted this reproductive rights slogan. The new title, It’s My Choice or C’est Mon Choix , was selected for its easy use in English and French. The PtDA leads the user through 6 sections:

• The Introduction section provides the user with information about the decision and the PtDA, as well as grids comparing positive and negative features of the abortion pill and procedure, including their chance of benefits (eg, effectiveness), harms (eg, complications), and other relevant factors (eg, number of appointments and cost).
• The About Me section asks the user to identify any contraindications to the methods. It then prompts users to consider their privacy needs and gives examples of how this relates to each option (eg, the abortion pill can be explained to others as a miscarriage; procedural care can be completed quickly).
• The My Values section includes a values clarification exercise, in which the user selects and weights (on a 0-100 scale) the relative importance of at least three of 7 decisional attributes: avoiding pain, avoiding bleeding, having the abortion at home, having an experience that feels like a miscarriage, having fewer appointments, less time off for recovery, and having a companion during the abortion.
• The My Choice section highlights 1 option, based on the attribute weights the user assigned in the My Values section. For instance, if a user strongly preferred to avoid bleeding and have fewer appointments, the software would suggest that a procedural abortion would be a better match. For a user who preferred having the abortion at home and having a companion present, the software would suggest that a medication abortion would be a better match. The user selects the option they prefer.
• The Review section asks the user to complete the 4-item SURE (Sure of Myself, Understand Information, Risk-Benefit Ratio, Encouragement) screening test [ 41 ], and advises them to talk with an expert if they answer “no” to any of the questions. This section also includes information phone lines to ensure that users can seek confidential, accurate, and nonjudgmental support.
• Lastly, in the Next Steps section, users see a summary of their choice and the features that matter most to them, instructions for how to save the results, keep the results private, and find an abortion health care professional. Each section of the PtDA includes a “Leave” button in case users need to navigate away from the website quickly.

We calculated readability by inputting the plain text of the web-based PtDA into a SMOG Index calculator [ 32 ], which assessed the reading level of the web-based PtDA as grade 9.2.

To ensure users’ trust in the information as accurate and unbiased we provided a data declaration on the landing page: “the clinical information presented in this decision aid comes from Society of Obstetricians and Gynaecologists best practice guidelines.” On the landing page, we also specify “This website was developed by researchers at the University of British Columbia and Dalhousie University. This tool is not supported or connected to any pharmaceutical company.”

A total of 50 participants, including 25 patients and 25 health care professionals, reviewed the PtDA website and completed the survey between January and March 2021. The majority of patient (n=23, 92%) and health care professional (n=23, 92%) participants identified as cisgender women. Among patient participants, 16% (n=4) reported one or more previous abortions in various clinical settings. More than half (n=16, 64%) of health care professionals offered care in private medical offices, with other locations including sexual health clinics, community health centers, and youth clinics. Many health care professionals were family physicians (n=11, 44%), and other common types were nurse practitioners (n=7, 28%) and midwives (n=3, 12%). The mean proportion of the clinical practice of each health care professional devoted to abortion care was 18% (SD 13%). Most health care professional respondents (n=18, 72%) were involved with the provision of medication, but not procedural, abortion care. The characteristics of patient and health care professional participants are reported in Table 3 .

a In total, 4 participants reported a history of abortion care, representing 6 abortion procedures.

b Not available.

The mean System Usability Score met the threshold for good usability among both patient (mean 85.7, SD 8.6) and health care professional (mean 80, SD 12) participants, although some health care professionals agreed with the statement, “I found the website to be unnecessarily complex,” (see Multimedia Appendix 3 for the full distribution of responses from patient and health care professionals). All 25 patients and 22 out of 25 (88%) health care professional respondents indicated that the user-friendliness of the PtDA was good or the best imaginable. When asked what they liked most about the PtDA, both participant groups described the ease of use, comparison of options, and the explicit values clarification exercise. When asked what they liked least about the PtDA, several health care professionals and some patients pointed out that it was difficult to use on a cell phone. A summary of usability results is presented in Table 4 .

In total, 21 (84%) patients and 18 (72%) health care professionals felt that the PtDA was not missing any information needed to decide about the method of abortion in early pregnancy. While acknowledging that it is “hard to balance being easy to read/understand while including enough accurate clinical information,” several health care professionals and some patients indicated that the PtDA was too long and repetitive. Among the 4 (16%) patient participants who felt information was missing, the most common suggestion was a tool for locating an abortion health care professional. The 7 (28%) health care professionals who felt information was missing primarily made suggestions about the medical information included in the PtDA (eg, listing midwives as health care professionals with abortion care in scope of practice and the appropriateness of gender-inclusive terminology) and the accessibility of information for various language and cultural groups.

a Not available.

Implementation

Participants viewed the PtDA as a positive addition to current resources. Patients with a history of abortion care described looking for the information on the internet and speaking with friends, family members, and health care professionals. Compared with these sources of information, many patients liked the credibility and anonymity of the PtDA, whereas some disliked that it was less personal than a conversation. Further, 18 (72%) health care professional participants said that the PtDA would add to or replace the resources they currently use in practice. Compared with these other resources, health care professionals liked that the PtDA could be explored by patients independently and that it would support them in thinking about the option that was best for them. The disadvantages of the PtDA compared with existing resources were the length—which health care professionals felt would make it difficult to use in a clinical interaction—and the lack of localized information. In total, 23 each (92%) of patient and health care professional participants felt that they would use the PtDA before a consultation.

Principal Results

We designed a web-based, interactive PtDA for the choice of method of abortion in early pregnancy [ 42 ], taking a user-centered approach that involved usability testing with 36 patients and 25 health care professionals. Both patient and health care professional participants indicated that the PtDA had good usability and would be a valuable resource for decision-making. This PtDA fills a critical need to support the autonomy of patients and shared decision-making with their health care professional related to the preference-sensitive choice of method of abortion.

Comparison With Prior Work

A 2017 systematic review and environmental scan found that existing PtDAs for the method of abortion are of suboptimal quality [ 9 ]. Of the 50 PtDAs identified, all but one were created without expertise in decision aid design (eg, abortion services, reproductive health organizations, and consumer health information organizations); however, the development process for this UK-based pamphlet-style PtDA was not reported. The remaining PtDAs were noninteractive websites, smartphone apps, and PDFs that were not tested with users. The authors found that the information about methods of abortion was presented in a disorganized, inconsistent, and unequal way. Subsequent work has found that existing PtDAs emphasize medical (versus social, emotional, and practical) attributes, do not include values clarification, and can be biased to persuade users of a certain method [ 13 ].

To address some of the challenges identified in the literature, we systematically structured and designed elements of the PtDA following newly proposed IPDAS criteria (eg, showing positive and negative features with equal detail) [ 33 ]. We included an explicit values-clarification exercise, which a recent meta-analysis found to decrease decisional conflict and values-incongruent choices [ 43 ].

We based the decision aid on comprehensive and up-to-date scientific evidence related to the effectiveness and safety of medication abortion and procedural abortion; however, less evidence was available for nonmedical attributes. For example, many existing PtDAs incorrectly frame privacy as a “factual advantage” of medication abortion [ 13 ]. To address this, we included privacy in the About Me section as something that means “different things to different people.” Similarly, evidence suggests that patients who do not feel appropriately informed about the pain associated with their method of abortion are less satisfied with their choice [ 44 , 45 ]; and the degree of pain experienced varies across options and among individuals. Following the suggestion of patient participants to include stories and recognizing that evidence for the inclusion of narratives in PtDAs is emerging [ 46 ], we elected to develop brief first-person qualitative descriptions of the pain experience. The inclusion of narratives in PtDAs may be effective in supporting patients to avoid surprise and regret, to minimize affective forecasting errors, and to “visualize” their health condition or treatment experience [ 46 ]. Guided by the narrative immersion model, our goal was to provide a “real-world preview” of the pain experience [ 47 ].

In addition to integrating user perspectives on the optimal tone, content, and format of the PtDA, user testing provided evidence to inform the future implementation of the PtDA. A clear barrier to the completion of the PtDA during the clinical encounter from the health care professional perspective was its length, supporting the finding of a recent rapid realist review, which theorized that health care professionals are less likely to use long or otherwise complex PtDAs that are difficult to integrate into routine practice [ 48 ]. However, 46 out of 50 (92%) participants endorsed the use of the PtDA by the patient alone before the initial consultation, which was aligned with the patient participant’s preference to take an active role in making the final decision about their method of abortion as well as the best practice of early, pre-encounter distribution of PtDAs [ 48 ].

A unique feature of this PtDA was that it resulted from a broader program of integrated knowledge translation designed to support access to medication abortion once mifepristone became available in Canada in 2017. Guided by the principle that including knowledge users in research yields results that are more relevant and useful [ 49 ], we developed the PtDA in response to a knowledge user need, involved health care professional users as partners in our research process, including as coauthors, and integrated feedback from the expert panel. This parallels a theory of PtDA implementation that proposes that early involvement of health care professionals in PtDA development “creates a sense of ownership, increases buy-in, helps to legitimize content, and ensures the PtDA (content and delivery) is consistent with current practice” thereby increasing the likelihood of PtDA integration into routine clinical settings [ 48 ].

Viewed through an integrated knowledge translation lens, our findings point toward future areas of work to support access to abortion in Canada. Several patient participants indicated a need for tools to identify health care professionals who offer abortion care. Some shared that their primary health care professionals did not offer medication abortion despite it being within their scope of practice, and instead referred them to an abortion clinic for methods of counseling and care. We addressed this challenge in the PtDA by including links to available resources, such as confidential phone lines that link patients to health care professionals in their region. On the website we also indicated that patient users could ask their primary care providers whether they provide abortion care; however, we acknowledge that this may place the patient in a vulnerable position if their health care professional is uncomfortable with, or unable to, provide this service for any reason. Future work should investigate opportunities to shorten the pathway to this time-sensitive care, including how to support patients who use the decision aid to act on their informed preference for the method of abortion. This work may involve developing a tool for patients to talk to their primary care provider about prescribing medication abortion.

Strengths and Limitations

Several factors affect the interpretation of our work. Although potential patient users participated in the iterative development process, the patient perspective was not represented in a formal advisory panel in the same way that the health care professional experts were. Participant characteristics collected for the think-aloud interviews demonstrated that our patient sample did not include people with lower education attainment, for whom the grade level and length of the PtDA could present a barrier [ 50 ]. Any transfer of the PtDA to jurisdictions outside Canada must consider how legal, regulatory, and other contextual factors affect the choice of the method of abortion. Since this study was completed, we have explored additional strategies to address these concerns, including additional user testing with people from equity-deserving groups, drop-down menus to adjust the level of detail, further plain language editing, and videos illustrating core content. Since the focus of this study was usability, we did not assess PtDA effectiveness, including impact on knowledge, decisional conflict, choice predisposition and decision, or concordance; however, a randomized controlled trial currently underway will measure the impact of the PtDA on these outcomes in a clinical setting. Finally, our integrated knowledge translation approach added to the robustness of our study by ensuring that health care professionals and patients were equal partners in the research process. One impact of this partnered approach is that our team has received funding support from Health Canada to implement the website on a national scale for people across Canada considering their abortion options [ 51 ].

Conclusions

The PtDA provides people choosing a method of early abortion and their health care professionals with a resource to understand methods of abortion available in the Canadian context and support to make a values-aligned choice. We designed the PtDA using a systematic approach that included both patient and health care professional participants to help ensure its relevance and usability. Our future work will seek to evaluate the implementation of the PtDA in clinical settings, create alternate formats to enhance accessibility, and develop a sustainable update policy. We will also continue to advance access to abortion care in Canada with our broader integrated knowledge translation program of research.

Acknowledgments

The authors thank the participants for contributing their time and expertise to the design of this tool. Family medicine residents CMB, NC, KD-L, and JS were supported by Sue Harris grants, Department of Family Practice, University of British Columbia. KJW was supported by the Vanier Scholar Award (2020-23). SM was supported by a Michael Smith Health Research BC Scholar Award (18270). WVN was supported by a Canadian Institutes of Health Research and Public Health Agency of Canada Chair in Applied Public Health Research (2014-2024, CPP-329455-107837). All grants underwent external peer review for scientific quality. The funders played no role in the design of this study, data collection, analysis, interpretation, or preparation of this paper.

Data Availability

Our ethics approval has specified the primary data is not available.

Authors' Contributions

KJW, SM, and MB conceived of and designed this study. CMB, NC, and KD-L led interview data collection, analysis, and interpretation with input from SM. RS and JS led survey data collection, analysis, and interpretation with input from SM and MB. AW, LCL, and WVN contributed to the synthesis and interpretation of results. KJW, SM, and LT wrote the first draft of this paper, and all authors contributed to this paper’s revisions and approved the final version.

Conflicts of Interest

None declared.

Patient decision aid prototype.

Raw data for pain narratives.

Full distribution of System Usability Scale scores for patients and providers.

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Abbreviations

Edited by T Leung; submitted 07.05.23; peer-reviewed by G Sebastian, R French, B Zikmund-Fisher; comments to author 11.01.24; revised version received 23.02.24; accepted 25.02.24; published 16.04.24.

©Kate J Wahl, Melissa Brooks, Logan Trenaman, Kirsten Desjardins-Lorimer, Carolyn M Bell, Nazgul Chokmorova, Romy Segall, Janelle Syring, Aleyah Williams, Linda C Li, Wendy V Norman, Sarah Munro. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.04.2024.

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