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- Data Collection | Definition, Methods & Examples
Data Collection | Definition, Methods & Examples
Published on June 5, 2020 by Pritha Bhandari . Revised on June 21, 2023.
Data collection is a systematic process of gathering observations or measurements. Whether you are performing research for business, governmental or academic purposes, data collection allows you to gain first-hand knowledge and original insights into your research problem .
While methods and aims may differ between fields, the overall process of data collection remains largely the same. Before you begin collecting data, you need to consider:
- The aim of the research
- The type of data that you will collect
- The methods and procedures you will use to collect, store, and process the data
To collect high-quality data that is relevant to your purposes, follow these four steps.
Table of contents
Step 1: define the aim of your research, step 2: choose your data collection method, step 3: plan your data collection procedures, step 4: collect the data, other interesting articles, frequently asked questions about data collection.
Before you start the process of data collection, you need to identify exactly what you want to achieve. You can start by writing a problem statement : what is the practical or scientific issue that you want to address and why does it matter?
Next, formulate one or more research questions that precisely define what you want to find out. Depending on your research questions, you might need to collect quantitative or qualitative data :
- Quantitative data is expressed in numbers and graphs and is analyzed through statistical methods .
- Qualitative data is expressed in words and analyzed through interpretations and categorizations.
If your aim is to test a hypothesis , measure something precisely, or gain large-scale statistical insights, collect quantitative data. If your aim is to explore ideas, understand experiences, or gain detailed insights into a specific context, collect qualitative data. If you have several aims, you can use a mixed methods approach that collects both types of data.
- Your first aim is to assess whether there are significant differences in perceptions of managers across different departments and office locations.
- Your second aim is to gather meaningful feedback from employees to explore new ideas for how managers can improve.
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Based on the data you want to collect, decide which method is best suited for your research.
- Experimental research is primarily a quantitative method.
- Interviews , focus groups , and ethnographies are qualitative methods.
- Surveys , observations, archival research and secondary data collection can be quantitative or qualitative methods.
Carefully consider what method you will use to gather data that helps you directly answer your research questions.
When you know which method(s) you are using, you need to plan exactly how you will implement them. What procedures will you follow to make accurate observations or measurements of the variables you are interested in?
For instance, if you’re conducting surveys or interviews, decide what form the questions will take; if you’re conducting an experiment, make decisions about your experimental design (e.g., determine inclusion and exclusion criteria ).
Sometimes your variables can be measured directly: for example, you can collect data on the average age of employees simply by asking for dates of birth. However, often you’ll be interested in collecting data on more abstract concepts or variables that can’t be directly observed.
Operationalization means turning abstract conceptual ideas into measurable observations. When planning how you will collect data, you need to translate the conceptual definition of what you want to study into the operational definition of what you will actually measure.
- You ask managers to rate their own leadership skills on 5-point scales assessing the ability to delegate, decisiveness and dependability.
- You ask their direct employees to provide anonymous feedback on the managers regarding the same topics.
You may need to develop a sampling plan to obtain data systematically. This involves defining a population , the group you want to draw conclusions about, and a sample, the group you will actually collect data from.
Your sampling method will determine how you recruit participants or obtain measurements for your study. To decide on a sampling method you will need to consider factors like the required sample size, accessibility of the sample, and timeframe of the data collection.
If multiple researchers are involved, write a detailed manual to standardize data collection procedures in your study.
This means laying out specific step-by-step instructions so that everyone in your research team collects data in a consistent way – for example, by conducting experiments under the same conditions and using objective criteria to record and categorize observations. This helps you avoid common research biases like omitted variable bias or information bias .
This helps ensure the reliability of your data, and you can also use it to replicate the study in the future.
Creating a data management plan
Before beginning data collection, you should also decide how you will organize and store your data.
- If you are collecting data from people, you will likely need to anonymize and safeguard the data to prevent leaks of sensitive information (e.g. names or identity numbers).
- If you are collecting data via interviews or pencil-and-paper formats, you will need to perform transcriptions or data entry in systematic ways to minimize distortion.
- You can prevent loss of data by having an organization system that is routinely backed up.
Finally, you can implement your chosen methods to measure or observe the variables you are interested in.
The closed-ended questions ask participants to rate their manager’s leadership skills on scales from 1–5. The data produced is numerical and can be statistically analyzed for averages and patterns.
To ensure that high quality data is recorded in a systematic way, here are some best practices:
- Record all relevant information as and when you obtain data. For example, note down whether or how lab equipment is recalibrated during an experimental study.
- Double-check manual data entry for errors.
- If you collect quantitative data, you can assess the reliability and validity to get an indication of your data quality.
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.
- Student’s t -distribution
- Normal distribution
- Null and Alternative Hypotheses
- Chi square tests
- Confidence interval
- Cluster sampling
- Stratified sampling
- Data cleansing
- Reproducibility vs Replicability
- Peer review
- Likert scale
- Implicit bias
- Framing effect
- Cognitive bias
- Placebo effect
- Hawthorne effect
- Hindsight bias
- Affect heuristic
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
When conducting research, collecting original data has significant advantages:
- You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
- You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )
However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
Reliability and validity are both about how well a method measures something:
- Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
- Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).
If you are doing experimental research, you also have to consider the internal and external validity of your experiment.
Operationalization 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, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.
Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
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Research and Writing Guides
Writing a paper? Don't get lost.
How to collect data for your thesis
After choosing a topic for your thesis , you’ll need to start gathering data. In this article, we focus on how to effectively collect theoretical and empirical data.
Empirical data : unique research that may be quantitative, qualitative, or mixed.
Theoretical data : secondary, scholarly sources like books and journal articles that provide theoretical context for your research.
Thesis : the culminating, multi-chapter project for a bachelor’s, master’s, or doctoral degree.
Qualitative data : info that cannot be measured, like observations and interviews .
Quantitative data : info that can be measured and written with numbers.
- Collecting theoretical data
At this point in your academic life, you are already acquainted with the ways of finding potential references. Some obvious sources of theoretical material are:
- edited volumes
- conference proceedings
- online databases like Google Scholar , ERIC , or Scopus
You can also take a look at the top list of academic search engines .
Search for theses on your topic
Looking at other theses on your topic can help you see what approaches have been taken and what aspects other writers have focused on. Pay close attention to the list of references and follow the bread-crumbs back to the original theories and specialized authors.
Use content-sharing platforms
Another method for gathering theoretical data is to read through content-sharing platforms. Many people share their papers and writings on these sites. You can either hunt sources, get some inspiration for your own work or even learn new angles of your topic.
Some popular content sharing sites are:
With these sites, you have to check the credibility of the sources. You can usually rely on the content, but we recommend double-checking just to be sure. Take a look at our guide on what are credible sources?
The more you know, the better. The guide, " How to undertake a literature search and review for dissertations and final year projects ," will give you all the tools needed for finding literature .
- Collecting empirical data
In order to successfully collect empirical data, you have to choose first what type of data you want as an outcome. There are essentially two options, qualitative or quantitative data. Many people mistake one term with the other, so it’s important to understand the differences between qualitative and quantitative research .
Boiled down, qualitative data means words and quantitative means numbers. Both types are considered primary sources . Whichever one adapts best to your research will define the type of methodology to carry out, so choose wisely.
Qualitative vs. Quantitative data
In the end, having in mind what type of outcome you intend and how much time you count on will lead you to choose the best type of empirical data for your research. For a detailed description of each methodology type mentioned above, read more about collecting data .
Once you gather enough theoretical and empirical data, you will need to start writing. But before the actual writing part, you have to structure your thesis to avoid getting lost in the sea of information. Take a look at our guide on how to structure your thesis for some tips and tricks.
- Frequently Asked Questions about gathering data for your thesis
The key to knowing what type of data you should collect for your thesis is knowing in advance the type of outcome you intend to have, and the amount of time you count with.
Some obvious sources of theoretical material are journals, libraries and online databases like Google Scholar , ERIC or Scopus , or take a look at the top list of academic search engines . You can also search for theses on your topic or read content sharing platforms, like Medium , Issuu , or Slideshare .
To gather empirical data, you have to choose first what type of data you want. There are two options, qualitative or quantitative data. You can gather data through observations, interviews, focus groups, or with surveys, tests, and existing databases.
Qualitative data means words, information that cannot be measured. It may involve multimedia material or non-textual data. This type of data claims to be detailed, nuanced and contextual.
Quantitative data means numbers, information that can be measured and written with numbers. This type of data claims to be credible, scientific and exact.
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Methods of Data Collection – Guide with Tips
Published by Carmen Troy at August 14th, 2021 , Revised On August 25, 2023
A key aspect of the dissertation writing process is to choose a method of data collection that would be recognised as independent and reliable in your field of study.
A well-rounded data collection method helps you communicate to the readers exactly how you would go about testing the research hypothesis or addressing the research questions – usually set out in the dissertation introduction chapter .
So what are the different methods of data collection you can use in your dissertation?
When choosing a dissertation method of data collection, there are certain elements you would need to keep in mind including the chosen topic, the established research aim and objectives, formulated research questions , and time and monetary limitations.
With several data collection methods to choose from, students often get confused about the most appropriate for their own research.
Here is a complete guide on the two research designs you can choose from in your dissertation – primary research and secondary research . The different research approaches within each of these two categories are explained below in detail.
Primary Research Strategy
Primary research involves data collection directly from participants. This data collection method is often chosen when the research is based on a certain area, a specific organisation, or a country.
Because the dissertation requires specific results and information, the primary research strategy is chosen to gather the required information and formulate results according to the research questions. There are various methods for conducting primary research:
Interviews are face-to-face discussions conducted directly with the participant(s). The matters raised during interviews are audio/video recorded or manually written down for subsequent analysis.
Participants are asked to fill and sign a consent form before conducting the interviews. All questions asked during the interview are related to the research only.
Participants have the complete right to remain anonymous or reveal personal details if appropriate. Interviews are one of the most commonly used data collection strategies for dissertations employed by researchers.
Interviews are a flexible type of research. There are three types of interviews, depending on the extent to which they are structured – structured interviews , semi-structured interviews , and informal/unstructured interviews .
- The researcher collects responses based on a set of established questions with little to no room for deviation from the pre-determined structure with structured interviews.
- Unstructured interviews do not require the researcher to have a set of pre-agreed questions for the interview. The scope of this type of interview includes comprehensive areas of discussion. Responses are gathered by employing techniques such as probing and prompting.
- Semi-structured interviews offer a balance between a formal interview’s focus and the flexibility of an unstructured interview.
- In either case, the participant is informed beforehand of the nature of the interview they will be involved in.
- While there is no strict rule concerning the number of participants an interview can involve, it would make sense to keep the group to 5-6 people. On the other hand, you can interview only one subject if that is more appropriate to your needs.
With the advent of technology, and to save time, many researchers now conduct online interviews and/or telephonic interviews. The timings and schedule are set before the day of the interview, and the participant is informed of the details via email. This helps in saving valuable time for the researcher, as well as the participant.
Not sure whether you should use primary or secondary research for your dissertation? Here is an article that provides all the information you need to decide whether you should choose primary or secondary research .
Surveys are another popular primary data collection method. The participants for this type of research design are chosen through a sampling method based on a selected population.
The researcher prepares a survey that consists of questions relating to the topic of research . These survey questions can be either open or close-ended .
Close-ended questions require the participant to choose from the multiple choices provided. If you are conducting a survey, you may decide not to meet the respondents due to financial or time constraints because surveys can be filled online or over a telephonic session.
On the other hand, open-ended questions do not have any options, and the respondent has the liberty to answer according to their own perception and understanding. For these types of surveys, meeting the participant in person would be the more fitting option.
Dissertations with close-ended questions are classified as quantitative research strategy dissertations. The data collected from these surveys are analysed through statistical tools such as SPSS or Excel.
Diverse tests are applied to the data depending on the research questions, aim, and objectives to reach a conclusion. For open-ended questions, qualitative analysis is conducted by thematic analysis and coding techniques.
- Surveys are frequently conducted in market research, social sciences, and commercial settings.
- Surveys can also be useful across a wide range of disciplines from business to anthropology.
Our writers have years of experience in dissertation research. Whether you need help with the full dissertation paper or just a part of it, Research Prospect writers can help you achieve your desired grade.
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Questionnaires are similar to closed-ended surveys. They contain standard questions and are distributed amongst a set of participants. A lot of researchers follow the Likert scale when using questionnaires.
This scale includes 5 options ranging from “strongly agree” to “strongly disagree”. The questionnaire consists of statements to which the respondents have to respond based on the specified options.
These responses are then analysed with the help of SPSS or another analytical tool by running analytical tests to create trend graphs and charts according to each statement’s responses.
This type of dissertation research design is usually used when the behaviour of a group of people or an individual is to be studied. The researcher observes the participants figure out how they behave in certain conditions.
There are two types of observations – overt and covert. Overt observation is usually adopted when observing individuals. Participants are aware that they are being observed, and they also sign a written consent form.
On the other hand, covert observation refers to observation without consent. The participant is not aware that researchers are studying them, and no formal consent forms are required to be signed.
This dissertation data collection method involves collecting data from a small group of people, usually limited to 8-10. The whole idea of focus groups is to bring together experts on the topic that is being investigated.
The researcher must play the role of a moderator to stimulate discussion between the focus group members. However, a focus group data collection strategy is viral among businesses and organisations who want to learn more about a certain niche market to identify a new group of potential consumers.
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Secondary Research Strategy
Secondary research is the other research approach for dissertations, and it is usually chosen for its cost-effectiveness. Secondary research refers to the study and analysis of already published material on the subject.
This means that when a research topic is finalised, the research question is formulated and aims and objectives set up; the researcher starts to look for research and studies conducted in the past on the same topic. Reviewing and analysing those studies helps understand the topic more effectively and relate previous results and conclusions.
Researchers carried out secondary research when there is limited or no access to the participants relating to the thesis problem , even though there could be other reasons to choose a secondary data collection strategy such as time constraints and the high cost of conducting primary research.
When using previous research, you should always be aware that they might have been carried out in a different setting, with different aim and objectives, thus they cannot exactly match the outcome of your dissertation.
Basing your findings solely on one study will undermine the reliability of your work. Do your research, understand your topic and look for other researchers’ views in your field of study. This will give you an idea as to how the topic has been studied in the past.
Reviewing and analysing different perspectives on the same topic will help you improve your understanding, and you’ll be able to think critically about everything you read.
A thorough critical analysis will help you present the previous research and studies to add weight to your research work.
Results and discussion of secondary research are based on the findings mentioned in the previous studies and what you learned while reviewing and analysing them. There is absolutely nothing wrong if your findings are different from others who investigated the same topic.
The sources for this type of research include existing literature and research material (usually extracted from government bodies, libraries, books, journals, or credible websites).
If you are still unsure about the different research strategies you can use in your dissertation, you might want to get some help from our writers who will offer free advice regarding which method of research you should base your dissertation on.
Would you like some help with your dissertation methodology? We have academic experts for all academic subjects, who can assist you no matter how urgent or complex your needs may be.
Research prospect can help you with irrespective of the dissertation’s length; it can be partial or full. Please fill out our simple order form to place your order for the dissertation chapter – methodology . Or find out more about our dissertation writing services .
Frequently Asked Questions
What are the different methods of data collection.
Different methods of data collection include:
- Surveys/questionnaires: Gather standardized responses.
- Interviews: Obtain in-depth qualitative insights.
- Observations: Study behaviour in natural settings.
- Experiments: Manipulate variables to analyze outcomes.
- Secondary sources: Utilize existing data or documents.
- Case studies: Investigate a single subject deeply.
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A meta-analysis is a formal, epidemiological, quantitative study design that uses statistical methods to generalise the findings of the selected independent studies.
Textual analysis is the method of analysing and understanding the text. We need to look carefully at the text to identify the writer’s context and message.
Discourse analysis is an essential aspect of studying a language. It is used in various disciplines of social science and humanities such as linguistic, sociolinguistics, and psycholinguistic.
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Qualitative Research: Data Collection, Analysis, and Management
In an earlier paper, 1 we presented an introduction to using qualitative research methods in pharmacy practice. In this article, we review some principles of the collection, analysis, and management of qualitative data to help pharmacists interested in doing research in their practice to continue their learning in this area. Qualitative research can help researchers to access the thoughts and feelings of research participants, which can enable development of an understanding of the meaning that people ascribe to their experiences. Whereas quantitative research methods can be used to determine how many people undertake particular behaviours, qualitative methods can help researchers to understand how and why such behaviours take place. Within the context of pharmacy practice research, qualitative approaches have been used to examine a diverse array of topics, including the perceptions of key stakeholders regarding prescribing by pharmacists and the postgraduation employment experiences of young pharmacists (see “Further Reading” section at the end of this article).
In the previous paper, 1 we outlined 3 commonly used methodologies: ethnography 2 , grounded theory 3 , and phenomenology. 4 Briefly, ethnography involves researchers using direct observation to study participants in their “real life” environment, sometimes over extended periods. Grounded theory and its later modified versions (e.g., Strauss and Corbin 5 ) use face-to-face interviews and interactions such as focus groups to explore a particular research phenomenon and may help in clarifying a less-well-understood problem, situation, or context. Phenomenology shares some features with grounded theory (such as an exploration of participants’ behaviour) and uses similar techniques to collect data, but it focuses on understanding how human beings experience their world. It gives researchers the opportunity to put themselves in another person’s shoes and to understand the subjective experiences of participants. 6 Some researchers use qualitative methodologies but adopt a different standpoint, and an example of this appears in the work of Thurston and others, 7 discussed later in this paper.
Qualitative work requires reflection on the part of researchers, both before and during the research process, as a way of providing context and understanding for readers. When being reflexive, researchers should not try to simply ignore or avoid their own biases (as this would likely be impossible); instead, reflexivity requires researchers to reflect upon and clearly articulate their position and subjectivities (world view, perspectives, biases), so that readers can better understand the filters through which questions were asked, data were gathered and analyzed, and findings were reported. From this perspective, bias and subjectivity are not inherently negative but they are unavoidable; as a result, it is best that they be articulated up-front in a manner that is clear and coherent for readers.
THE PARTICIPANT’S VIEWPOINT
What qualitative study seeks to convey is why people have thoughts and feelings that might affect the way they behave. Such study may occur in any number of contexts, but here, we focus on pharmacy practice and the way people behave with regard to medicines use (e.g., to understand patients’ reasons for nonadherence with medication therapy or to explore physicians’ resistance to pharmacists’ clinical suggestions). As we suggested in our earlier article, 1 an important point about qualitative research is that there is no attempt to generalize the findings to a wider population. Qualitative research is used to gain insights into people’s feelings and thoughts, which may provide the basis for a future stand-alone qualitative study or may help researchers to map out survey instruments for use in a quantitative study. It is also possible to use different types of research in the same study, an approach known as “mixed methods” research, and further reading on this topic may be found at the end of this paper.
The role of the researcher in qualitative research is to attempt to access the thoughts and feelings of study participants. This is not an easy task, as it involves asking people to talk about things that may be very personal to them. Sometimes the experiences being explored are fresh in the participant’s mind, whereas on other occasions reliving past experiences may be difficult. However the data are being collected, a primary responsibility of the researcher is to safeguard participants and their data. Mechanisms for such safeguarding must be clearly articulated to participants and must be approved by a relevant research ethics review board before the research begins. Researchers and practitioners new to qualitative research should seek advice from an experienced qualitative researcher before embarking on their project.
Whatever philosophical standpoint the researcher is taking and whatever the data collection method (e.g., focus group, one-to-one interviews), the process will involve the generation of large amounts of data. In addition to the variety of study methodologies available, there are also different ways of making a record of what is said and done during an interview or focus group, such as taking handwritten notes or video-recording. If the researcher is audio- or video-recording data collection, then the recordings must be transcribed verbatim before data analysis can begin. As a rough guide, it can take an experienced researcher/transcriber 8 hours to transcribe one 45-minute audio-recorded interview, a process than will generate 20–30 pages of written dialogue.
Many researchers will also maintain a folder of “field notes” to complement audio-taped interviews. Field notes allow the researcher to maintain and comment upon impressions, environmental contexts, behaviours, and nonverbal cues that may not be adequately captured through the audio-recording; they are typically handwritten in a small notebook at the same time the interview takes place. Field notes can provide important context to the interpretation of audio-taped data and can help remind the researcher of situational factors that may be important during data analysis. Such notes need not be formal, but they should be maintained and secured in a similar manner to audio tapes and transcripts, as they contain sensitive information and are relevant to the research. For more information about collecting qualitative data, please see the “Further Reading” section at the end of this paper.
DATA ANALYSIS AND MANAGEMENT
If, as suggested earlier, doing qualitative research is about putting oneself in another person’s shoes and seeing the world from that person’s perspective, the most important part of data analysis and management is to be true to the participants. It is their voices that the researcher is trying to hear, so that they can be interpreted and reported on for others to read and learn from. To illustrate this point, consider the anonymized transcript excerpt presented in Appendix 1 , which is taken from a research interview conducted by one of the authors (J.S.). We refer to this excerpt throughout the remainder of this paper to illustrate how data can be managed, analyzed, and presented.
Interpretation of Data
Interpretation of the data will depend on the theoretical standpoint taken by researchers. For example, the title of the research report by Thurston and others, 7 “Discordant indigenous and provider frames explain challenges in improving access to arthritis care: a qualitative study using constructivist grounded theory,” indicates at least 2 theoretical standpoints. The first is the culture of the indigenous population of Canada and the place of this population in society, and the second is the social constructivist theory used in the constructivist grounded theory method. With regard to the first standpoint, it can be surmised that, to have decided to conduct the research, the researchers must have felt that there was anecdotal evidence of differences in access to arthritis care for patients from indigenous and non-indigenous backgrounds. With regard to the second standpoint, it can be surmised that the researchers used social constructivist theory because it assumes that behaviour is socially constructed; in other words, people do things because of the expectations of those in their personal world or in the wider society in which they live. (Please see the “Further Reading” section for resources providing more information about social constructivist theory and reflexivity.) Thus, these 2 standpoints (and there may have been others relevant to the research of Thurston and others 7 ) will have affected the way in which these researchers interpreted the experiences of the indigenous population participants and those providing their care. Another standpoint is feminist standpoint theory which, among other things, focuses on marginalized groups in society. Such theories are helpful to researchers, as they enable us to think about things from a different perspective. Being aware of the standpoints you are taking in your own research is one of the foundations of qualitative work. Without such awareness, it is easy to slip into interpreting other people’s narratives from your own viewpoint, rather than that of the participants.
To analyze the example in Appendix 1 , we will adopt a phenomenological approach because we want to understand how the participant experienced the illness and we want to try to see the experience from that person’s perspective. It is important for the researcher to reflect upon and articulate his or her starting point for such analysis; for example, in the example, the coder could reflect upon her own experience as a female of a majority ethnocultural group who has lived within middle class and upper middle class settings. This personal history therefore forms the filter through which the data will be examined. This filter does not diminish the quality or significance of the analysis, since every researcher has his or her own filters; however, by explicitly stating and acknowledging what these filters are, the researcher makes it easer for readers to contextualize the work.
Transcribing and Checking
For the purposes of this paper it is assumed that interviews or focus groups have been audio-recorded. As mentioned above, transcribing is an arduous process, even for the most experienced transcribers, but it must be done to convert the spoken word to the written word to facilitate analysis. For anyone new to conducting qualitative research, it is beneficial to transcribe at least one interview and one focus group. It is only by doing this that researchers realize how difficult the task is, and this realization affects their expectations when asking others to transcribe. If the research project has sufficient funding, then a professional transcriber can be hired to do the work. If this is the case, then it is a good idea to sit down with the transcriber, if possible, and talk through the research and what the participants were talking about. This background knowledge for the transcriber is especially important in research in which people are using jargon or medical terms (as in pharmacy practice). Involving your transcriber in this way makes the work both easier and more rewarding, as he or she will feel part of the team. Transcription editing software is also available, but it is expensive. For example, ELAN (more formally known as EUDICO Linguistic Annotator, developed at the Technical University of Berlin) 8 is a tool that can help keep data organized by linking media and data files (particularly valuable if, for example, video-taping of interviews is complemented by transcriptions). It can also be helpful in searching complex data sets. Products such as ELAN do not actually automatically transcribe interviews or complete analyses, and they do require some time and effort to learn; nonetheless, for some research applications, it may be a valuable to consider such software tools.
All audio recordings should be transcribed verbatim, regardless of how intelligible the transcript may be when it is read back. Lines of text should be numbered. Once the transcription is complete, the researcher should read it while listening to the recording and do the following: correct any spelling or other errors; anonymize the transcript so that the participant cannot be identified from anything that is said (e.g., names, places, significant events); insert notations for pauses, laughter, looks of discomfort; insert any punctuation, such as commas and full stops (periods) (see Appendix 1 for examples of inserted punctuation), and include any other contextual information that might have affected the participant (e.g., temperature or comfort of the room).
Dealing with the transcription of a focus group is slightly more difficult, as multiple voices are involved. One way of transcribing such data is to “tag” each voice (e.g., Voice A, Voice B). In addition, the focus group will usually have 2 facilitators, whose respective roles will help in making sense of the data. While one facilitator guides participants through the topic, the other can make notes about context and group dynamics. More information about group dynamics and focus groups can be found in resources listed in the “Further Reading” section.
Reading between the Lines
During the process outlined above, the researcher can begin to get a feel for the participant’s experience of the phenomenon in question and can start to think about things that could be pursued in subsequent interviews or focus groups (if appropriate). In this way, one participant’s narrative informs the next, and the researcher can continue to interview until nothing new is being heard or, as it says in the text books, “saturation is reached”. While continuing with the processes of coding and theming (described in the next 2 sections), it is important to consider not just what the person is saying but also what they are not saying. For example, is a lengthy pause an indication that the participant is finding the subject difficult, or is the person simply deciding what to say? The aim of the whole process from data collection to presentation is to tell the participants’ stories using exemplars from their own narratives, thus grounding the research findings in the participants’ lived experiences.
Smith 9 suggested a qualitative research method known as interpretative phenomenological analysis, which has 2 basic tenets: first, that it is rooted in phenomenology, attempting to understand the meaning that individuals ascribe to their lived experiences, and second, that the researcher must attempt to interpret this meaning in the context of the research. That the researcher has some knowledge and expertise in the subject of the research means that he or she can have considerable scope in interpreting the participant’s experiences. Larkin and others 10 discussed the importance of not just providing a description of what participants say. Rather, interpretative phenomenological analysis is about getting underneath what a person is saying to try to truly understand the world from his or her perspective.
Once all of the research interviews have been transcribed and checked, it is time to begin coding. Field notes compiled during an interview can be a useful complementary source of information to facilitate this process, as the gap in time between an interview, transcribing, and coding can result in memory bias regarding nonverbal or environmental context issues that may affect interpretation of data.
Coding refers to the identification of topics, issues, similarities, and differences that are revealed through the participants’ narratives and interpreted by the researcher. This process enables the researcher to begin to understand the world from each participant’s perspective. Coding can be done by hand on a hard copy of the transcript, by making notes in the margin or by highlighting and naming sections of text. More commonly, researchers use qualitative research software (e.g., NVivo, QSR International Pty Ltd; www.qsrinternational.com/products_nvivo.aspx ) to help manage their transcriptions. It is advised that researchers undertake a formal course in the use of such software or seek supervision from a researcher experienced in these tools.
Returning to Appendix 1 and reading from lines 8–11, a code for this section might be “diagnosis of mental health condition”, but this would just be a description of what the participant is talking about at that point. If we read a little more deeply, we can ask ourselves how the participant might have come to feel that the doctor assumed he or she was aware of the diagnosis or indeed that they had only just been told the diagnosis. There are a number of pauses in the narrative that might suggest the participant is finding it difficult to recall that experience. Later in the text, the participant says “nobody asked me any questions about my life” (line 19). This could be coded simply as “health care professionals’ consultation skills”, but that would not reflect how the participant must have felt never to be asked anything about his or her personal life, about the participant as a human being. At the end of this excerpt, the participant just trails off, recalling that no-one showed any interest, which makes for very moving reading. For practitioners in pharmacy, it might also be pertinent to explore the participant’s experience of akathisia and why this was left untreated for 20 years.
One of the questions that arises about qualitative research relates to the reliability of the interpretation and representation of the participants’ narratives. There are no statistical tests that can be used to check reliability and validity as there are in quantitative research. However, work by Lincoln and Guba 11 suggests that there are other ways to “establish confidence in the ‘truth’ of the findings” (p. 218). They call this confidence “trustworthiness” and suggest that there are 4 criteria of trustworthiness: credibility (confidence in the “truth” of the findings), transferability (showing that the findings have applicability in other contexts), dependability (showing that the findings are consistent and could be repeated), and confirmability (the extent to which the findings of a study are shaped by the respondents and not researcher bias, motivation, or interest).
One way of establishing the “credibility” of the coding is to ask another researcher to code the same transcript and then to discuss any similarities and differences in the 2 resulting sets of codes. This simple act can result in revisions to the codes and can help to clarify and confirm the research findings.
Theming refers to the drawing together of codes from one or more transcripts to present the findings of qualitative research in a coherent and meaningful way. For example, there may be examples across participants’ narratives of the way in which they were treated in hospital, such as “not being listened to” or “lack of interest in personal experiences” (see Appendix 1 ). These may be drawn together as a theme running through the narratives that could be named “the patient’s experience of hospital care”. The importance of going through this process is that at its conclusion, it will be possible to present the data from the interviews using quotations from the individual transcripts to illustrate the source of the researchers’ interpretations. Thus, when the findings are organized for presentation, each theme can become the heading of a section in the report or presentation. Underneath each theme will be the codes, examples from the transcripts, and the researcher’s own interpretation of what the themes mean. Implications for real life (e.g., the treatment of people with chronic mental health problems) should also be given.
In this final section of this paper, we describe some ways of drawing together or “synthesizing” research findings to represent, as faithfully as possible, the meaning that participants ascribe to their life experiences. This synthesis is the aim of the final stage of qualitative research. For most readers, the synthesis of data presented by the researcher is of crucial significance—this is usually where “the story” of the participants can be distilled, summarized, and told in a manner that is both respectful to those participants and meaningful to readers. There are a number of ways in which researchers can synthesize and present their findings, but any conclusions drawn by the researchers must be supported by direct quotations from the participants. In this way, it is made clear to the reader that the themes under discussion have emerged from the participants’ interviews and not the mind of the researcher. The work of Latif and others 12 gives an example of how qualitative research findings might be presented.
Planning and Writing the Report
As has been suggested above, if researchers code and theme their material appropriately, they will naturally find the headings for sections of their report. Qualitative researchers tend to report “findings” rather than “results”, as the latter term typically implies that the data have come from a quantitative source. The final presentation of the research will usually be in the form of a report or a paper and so should follow accepted academic guidelines. In particular, the article should begin with an introduction, including a literature review and rationale for the research. There should be a section on the chosen methodology and a brief discussion about why qualitative methodology was most appropriate for the study question and why one particular methodology (e.g., interpretative phenomenological analysis rather than grounded theory) was selected to guide the research. The method itself should then be described, including ethics approval, choice of participants, mode of recruitment, and method of data collection (e.g., semistructured interviews or focus groups), followed by the research findings, which will be the main body of the report or paper. The findings should be written as if a story is being told; as such, it is not necessary to have a lengthy discussion section at the end. This is because much of the discussion will take place around the participants’ quotes, such that all that is needed to close the report or paper is a summary, limitations of the research, and the implications that the research has for practice. As stated earlier, it is not the intention of qualitative research to allow the findings to be generalized, and therefore this is not, in itself, a limitation.
Planning out the way that findings are to be presented is helpful. It is useful to insert the headings of the sections (the themes) and then make a note of the codes that exemplify the thoughts and feelings of your participants. It is generally advisable to put in the quotations that you want to use for each theme, using each quotation only once. After all this is done, the telling of the story can begin as you give your voice to the experiences of the participants, writing around their quotations. Do not be afraid to draw assumptions from the participants’ narratives, as this is necessary to give an in-depth account of the phenomena in question. Discuss these assumptions, drawing on your participants’ words to support you as you move from one code to another and from one theme to the next. Finally, as appropriate, it is possible to include examples from literature or policy documents that add support for your findings. As an exercise, you may wish to code and theme the sample excerpt in Appendix 1 and tell the participant’s story in your own way. Further reading about “doing” qualitative research can be found at the end of this paper.
Qualitative research can help researchers to access the thoughts and feelings of research participants, which can enable development of an understanding of the meaning that people ascribe to their experiences. It can be used in pharmacy practice research to explore how patients feel about their health and their treatment. Qualitative research has been used by pharmacists to explore a variety of questions and problems (see the “Further Reading” section for examples). An understanding of these issues can help pharmacists and other health care professionals to tailor health care to match the individual needs of patients and to develop a concordant relationship. Doing qualitative research is not easy and may require a complete rethink of how research is conducted, particularly for researchers who are more familiar with quantitative approaches. There are many ways of conducting qualitative research, and this paper has covered some of the practical issues regarding data collection, analysis, and management. Further reading around the subject will be essential to truly understand this method of accessing peoples’ thoughts and feelings to enable researchers to tell participants’ stories.
Appendix 1. Excerpt from a sample transcript
The participant (age late 50s) had suffered from a chronic mental health illness for 30 years. The participant had become a “revolving door patient,” someone who is frequently in and out of hospital. As the participant talked about past experiences, the researcher asked:
- What was treatment like 30 years ago?
- Umm—well it was pretty much they could do what they wanted with you because I was put into the er, the er kind of system er, I was just on
- endless section threes.
- But what I didn’t realize until later was that if you haven’t actually posed a threat to someone or yourself they can’t really do that but I didn’t know
- that. So wh-when I first went into hospital they put me on the forensic ward ’cause they said, “We don’t think you’ll stay here we think you’ll just
- run-run away.” So they put me then onto the acute admissions ward and – er – I can remember one of the first things I recall when I got onto that
- ward was sitting down with a er a Dr XXX. He had a book this thick [gestures] and on each page it was like three questions and he went through
- all these questions and I answered all these questions. So we’re there for I don’t maybe two hours doing all that and he asked me he said “well
- when did somebody tell you then that you have schizophrenia” I said “well nobody’s told me that” so he seemed very surprised but nobody had
- actually [pause] whe-when I first went up there under police escort erm the senior kind of consultants people I’d been to where I was staying and
- ermm so er [pause] I . . . the, I can remember the very first night that I was there and given this injection in this muscle here [gestures] and just
- having dreadful side effects the next day I woke up [pause]
- . . . and I suffered that akathesia I swear to you, every minute of every day for about 20 years.
- Oh how awful.
- And that side of it just makes life impossible so the care on the wards [pause] umm I don’t know it’s kind of, it’s kind of hard to put into words
- [pause]. Because I’m not saying they were sort of like not friendly or interested but then nobody ever seemed to want to talk about your life [pause]
- nobody asked me any questions about my life. The only questions that came into was they asked me if I’d be a volunteer for these student exams
- and things and I said “yeah” so all the questions were like “oh what jobs have you done,” er about your relationships and things and er but
- nobody actually sat down and had a talk and showed some interest in you as a person you were just there basically [pause] um labelled and you
- know there was there was [pause] but umm [pause] yeah . . .
This article is the 10th in the CJHP Research Primer Series, an initiative of the CJHP Editorial Board and the CSHP Research Committee. The planned 2-year series is intended to appeal to relatively inexperienced researchers, with the goal of building research capacity among practising pharmacists. The articles, presenting simple but rigorous guidance to encourage and support novice researchers, are being solicited from authors with appropriate expertise.
Previous articles in this series:
Bond CM. The research jigsaw: how to get started. Can J Hosp Pharm . 2014;67(1):28–30.
Tully MP. Research: articulating questions, generating hypotheses, and choosing study designs. Can J Hosp Pharm . 2014;67(1):31–4.
Loewen P. Ethical issues in pharmacy practice research: an introductory guide. Can J Hosp Pharm. 2014;67(2):133–7.
Tsuyuki RT. Designing pharmacy practice research trials. Can J Hosp Pharm . 2014;67(3):226–9.
Bresee LC. An introduction to developing surveys for pharmacy practice research. Can J Hosp Pharm . 2014;67(4):286–91.
Gamble JM. An introduction to the fundamentals of cohort and case–control studies. Can J Hosp Pharm . 2014;67(5):366–72.
Austin Z, Sutton J. Qualitative research: getting started. C an J Hosp Pharm . 2014;67(6):436–40.
Houle S. An introduction to the fundamentals of randomized controlled trials in pharmacy research. Can J Hosp Pharm . 2014; 68(1):28–32.
Charrois TL. Systematic reviews: What do you need to know to get started? Can J Hosp Pharm . 2014;68(2):144–8.
Competing interests: None declared.
Examples of qualitative research in pharmacy practice.
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