Yes, using existing theory to define your codes is a deductive approach, but the real issue is: What are your research questions? Does the Health Beliefs Model specify anything like independent or dependent variables, or is it basically descriptive?

it is qualitative. What are your influencing factors for and against betal chewing. So I will give an example one of the participants said that he cannot stop betel as his peers engage in it, I took it as a code for peer influnce and converetd it the theme of percieved barrier?

Is this my flow correct or not

Hi Sameera, yes, from what you describe, you use a deductive approach to analyzing your data. From theory to data. Regarding this approach, I recommend you review texts on qualitative content analysis by Philipp Mayring, in which you can find out how from predefined categories you analyze your data. However, I also recommend adopting an abductive approach to analysis, which would allow you to go from theory to data and from data to theory, in a game of constant interpretation.

I think the key element of a deductive system is that it generates your actual code categories. In this case, it seems like the HBM mostly generates a higher order organizing framework for your codes based on concepts like barriers and facilitators.

In my candid opinion, you are not wrong. However, it will depend on your research questions directly connected to the hypothesis.

I agree with Ambrues Monboe Nebo who states that "it will depend on your research questions directly connected to the hypothesis." Here is a brief article which should be helpful as you conceptuaize and plan your scientific research.

This is the paragraph which is most relevant to your ResearchGate discussion question: "Choice between deductive and inductive approaches

Deductive research approach explores a known theory or phenomenon and tests if that theory is valid in given circumstances. It has been noted that “the deductive approach follows the path of logic most closely. The reasoning starts with a theory and leads to a new hypothesis. This hypothesis is put to the test by confronting it with observations that either lead to a confirmation or a rejection of the hypothesis”[4].Moreover, deductive reasoning can be explained as “reasoning from the general to the particular”[5], whereas inductive reasoning is the opposite. In other words, deductive approach involves formulation of hypotheses and their subjection to testing during the research process, while inductive studies do not deal with hypotheses in any ways."

Source link: https://research-methodology.net/research-methodology/research-approach/deductive-approach-2/

"Deductive Approach (Deductive Reasoning) A deductive approach is concerned with “developing a hypothesis (or hypotheses) based on existing theory, and then designing a research strategy to test the hypothesis”[1]It has been stated that “deductive means reasoning from the particular to the general. If a causal relationship or link seems to be implied by a particular theory or case example, it might be true in many cases. A deductive design might test to see if this relationship or link did obtain on more general circumstances”[2].Deductive approach can be explained by the means of hypotheses, which can be derived from the propositions of the theory. In other words, deductive approach is concerned with deducting conclusions from premises or propositions.

Deduction begins with an expected pattern “that is tested against observations, whereas induction begins with observations and seeks to find a pattern within them”[3].

Advantages of Deductive Approach Deductive approach offers the following advantages:

Possibility to explain causal relationships between concepts and variables Possibility to measure concepts quantitatively Possibility to generalize research findings to a certain extent Alternative to deductive approach is inductive approach. The table below guides the choice of specific approach depending on circumstances:

Deductive approach preferred

Inductive approach preferred

Wealth of literature

Abundance of sources

Scarcity of sources

Time availability

Short time available to complete the study

There is no shortage of time to compete the study

Risk To avoid risk

Risk is accepted, no theory may emerge at all

Choice between deductive and inductive approaches

Deductive research approach explores a known theory or phenomenon and tests if that theory is valid in given circumstances. It has been noted that “the deductive approach follows the path of logic most closely. The reasoning starts with a theory and leads to a new hypothesis. This hypothesis is put to the test by confronting it with observations that either lead to a confirmation or a rejection of the hypothesis”[4].Moreover, deductive reasoning can be explained as “reasoning from the general to the particular”[5], whereas inductive reasoning is the opposite. In other words, deductive approach involves formulation of hypotheses and their subjection to testing during the research process, while inductive studies do not deal with hypotheses in any ways.

Application of Deductive Approach (Deductive Reasoning) in Business Research In studies with deductive approach, the researcher formulates a set of hypotheses at the start of the research. Then, relevant research methods are chosen and applied to test the hypotheses to prove them right or wrong.📷Generally, studies using deductive approach follow the following stages:Deducing hypothesis from theory. Formulating hypothesis in operational terms and proposing relationships between two specific variables Testing hypothesis with the application of relevant method(s). These are quantitative methods such as regression and correlation analysis, mean, mode and median and others. Examining the outcome of the test, and thus confirming or rejecting the theory. When analysing the outcome of tests, it is important to compare research findings with the literature review findings. Modifying theory in instances when hypothesis is not confirmed. My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance contains discussions of theory and application of research approaches. The e-book also explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research design, methods of data collection, data analysis and sampling are explained in this e-book in simple words.John Dudovskiy📷[1] Wilson, J. (2010) “Essentials of Business Research: A Guide to Doing Your Research Project” SAGE Publications, p.7[2] Gulati, PM, 2009, Research Management: Fundamental and Applied Research, Global India Publications, p.42[3] Babbie, E. R. (2010) “The Practice of Social Research” Cengage Learning, p.52[4] Snieder, R. & Larner, K. (2009) “The Art of Being a Scientist: A Guide for Graduate Students and their Mentors”, Cambridge University Press, p.16[5] Pelissier, R. (2008) “Business Research Made Easy” Juta & Co., p.3.

Source link: https://research-methodology.net/research-methodology/research-approach/deductive-approach-2/

As part of your "brainstorming," you may wish to read this web page article:

https://www.andreajbingham.com/resources-tips-and-tricks/deductive-and-inductive-approaches-to-qualitative-analysis

Current Page: /Resources, Tips, and Tricks / Contact Me

"Qualitative analysis: Deductive and inductive approaches" Written By Andrea J. Bingham, Ph.D.

"How you analyze qualitative data depends largely on your methodology, your personal organizational and analytic preferences, and what kind of data you have. That being said, all qualitative data analysis processes are going to fall into one of two categories: deductive or inductive. In this post, I’m going outline what each of those terms mean for qualitative analysis, and discuss some general deductive and inductive analytic strategies. Some of what appears here comes from a book chapter I wrote with Dr. Patty Witkowsky on inductive and deductive approaches to qualitative data analysis. The chapter appears in Vanover, Mihas, and Saldaña’s book Analyzing and Interpreting Qualitative Research: After the Interview (Bingham & Witkowsky, 2021).The material presented here can be cited as:Bingham, A.J., & Witkowsky, P. (2022). Deductive and inductive approaches to qualitative data analysis. In C. Vanover, P. Mihas, & J. Saldaña (Eds.), Analyzing and interpreting qualitative data: After the interview (pp. 133-146). SAGE Publications.

Deductive AnalysisDeductive, or a priori, analysis generally means applying theory to the data to test the theory. It’s a kind of “top-down” approach to data analysis. In qualitative analysis, this often means applying predetermined codes to the data. The codes can be developed as strictly organizational tools, or they can be created from concepts drawn from the literature, from theory, or from propositions that the researcher has developed.

Deductive analysis can help you to: Sort data into organizational categories, such as data type, participant, or time period. To do this, you can develop attribute codes (Miles et al., 2020) to organize your data. These attribute codes are applied to categorize your data by data type (e.g., “interview”), location (e.g., “Binary High School”), participant (e.g., “Mr. Perez”), time period ( e.g., “Fall 2017”), etc. I generally do this as a first cycle of coding to create an organizational schema. Organize data into categories to maintain alignment with research questions. Deductive analysis can help you maintain focus on the purpose of your research. Qualitative data can get…unwieldy. So, it’s helpful to have a plan to stay focused on your research questions. To do this, during my first read-through of my data, I create broad topical categories of interest based on my research questions and then sort the data into those categories. For example, if I’m doing study of how teachers’ implement technology-facilitated competency-based learning practices in their classrooms, I might develop the codes “Classroom practice,” “Assessment,” “Technology,” and “Data use” to reflect the broad topics of my research. I then sort the data into those categories, which allows me to focus on relevant data in subsequent rounds of analysis. Apply theoretical or conceptual frameworks. Deductive practices can also help researchers to apply theory or conceptual frameworks. For me, this process generally comes after I do some inductive analysis of my data to identify themes, but you could draw on these strategies at really any point in the analysis process. For my process, I create codes based on the components of my theoretical framework, and then sort my data into those predetermined theory-based categories. Theory-based codes from institutional theory, for example, might include “Isomorphism” or “Decoupling.”

Inductive Analysis

Inductive analysis, on the other hand, is a more emergent strategy, where the researcher reads through the data and allows codes to emerge/names concepts as they emerge. It’s more of a “bottom-up” analytic strategy. There are many forms of inductive analysis, but some common practices are open coding (sometimes called initial coding), in vivo coding (codes developed from participants’ own words), and constant comparative analysis. Memoing plays a key role for me as well. I memo to keep track of my analysis process and the decisions I make and to make sense of the data I’m reading. I also keep a running memo of the themes and findings I am starting to see, and I have a memo where I keep interesting or generative participant quotes or excerpts from field notes, and any evidence relevant for my themes and findings as they develop.

Inductive analysis can help you to: Make meaning from the data. Because I typically use some deductive coding strategies to organize my data first, and sort it into categories that are relevant to my study purpose, my inductive analysis process generally starts after I’ve already done a pass through my data. However, you could start with inductive analysis (though I still recommend some attribute coding first to help you keep organized). When I start my cycle of inductive analysis, I finally begin to make meaning of the data I have. For me, this generally starts with open coding - a pretty classic form of qualitative coding during which the researcher reads through the data and develops and applies codes as they go, to represent what’s happening in the data. I read through the data in each category I created in my first round of deductive coding, creating and applying codes and identifying emerging topics or concepts as I read. I then use what’s called “pattern coding” to identify patterns across and within data sources. This is a process of condensing the codes created during open coding to chunk the data into fewer analytic concepts. This helps me begin to summarize the data. Develop themes and findings. The key purpose of inductive analysis is to really dig into what is happening in the data, to understand the themes present in the data and to produce findings to answer your research questions. In my analysis process, I identify themes from the pattern codes through memoing and further condensing the pattern codes where I can. I then try to capture the themes in short phrases like “Real time data use” or “technology-facilitated competency-based assessment.” Many qualitative researchers use the words “themes” and “findings” interchangeably, which works for them. For me, I like to differentiate. My themes are usually words or phrases, and I develop my findings from those themes, by condensing and rewording the themes into short phrases that clearly answer the research questions. For example, “Teachers relied on real time data use to implement competency-based learning” would be a finding for the research question “How do teachers implement competency-based learning in their classrooms?” Identify representative data to support findings. Throughout my analysis process, I will often develop in vivo codes from participants’ own words to point to data that is representative of particular findings. I also keep a running memo of participant quotes and excerpts from field notes, etc., as well as a memo of my emerging findings, where I will note representative evidence and write deeper descriptions and explanations. This process helps me to keep track of important evidence, and gives me a place to free write about my findings. I am a person who thinks best through writing, so I find this memoing process especially critical. Explain findings using theory and literature. During one of my deductive cycles of coding mentioned above, I apply codes based on my theoretical framework(s) and/or the existing literature. But that doesn’t go far enough in terms of really applying theory and using it to make sense of and explain the findings (and write the discussion section). So, after the deductive cycle of coding in which I sort the data into theory-based categories, I do some inductive analysis, where I memo to develop short phrases that connect my findings with theory and existing literature. Though coding forms the basis for most of my analysis, memoing in this cycle helps me understand what it all means and why anyone should care about it. Combining deductive and inductive coding and memoing supports the development of the discussion and implications sections. It also helps you to understand your findings in relation to existing research, examine how the theoretical framework explains the findings (and where it doesn’t, which allows for theoretical contributions), and can support you in providing actionable, meaningful implications and recommendations.

As I see it, both deductive and inductive strategies are important in qualitative analysis, so in my work, I draw on both. I use deductive strategies to organize and focus myself, and I use inductive strategies to understand what is happening in the data, without forcing the data into what I think I’ll see. In short, a data analysis process that draws on both deductive and inductive analysis supports a more organized, rigorous, and analytically sound qualitative study.

See below for an example of how I organize deductive and inductive analytic practices into cycles.

📷This figure, adapted from Bingham & Witkowsky (2021) and Bingham (Under review), gives an overview of my analysis process. Five cycles, encompassing both deductive and inductive processes.

The material presented here can be cited as:Bingham, A.J., & Witkowsky, P. (2022). Deductive and inductive approaches to qualitative data analysis. In C. Vanover, P. Mihas, & J. Saldaña (Eds.), Analyzing and interpreting qualitative data: After the interview (pp. 133-146). SAGE Publications.

SOURCE LINK: https://www.andreajbingham.com/resources-tips-and-tricks/deductive-and-inductive-approaches-to-qualitative-analysis

Since your main topic is related to health science, you might find it useful to read the article at this link: https://ebn.bmj.com/content/21/3/63

Here is a scientific article on "Methods of data collection in qualitative research: interviews and focus groups," which may give you some new ideas!

"Nature

Methods of data collection in qualitative research: interviews and focus groups

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https://www.nature.com/articles/bdj.2008.192#article-info

Published: 22 March 2008 Methods of data collection in qualitative research: interviews and focus groups P. Gill, K. Stewart, E. Treasure & B. Chadwick British Dental Journal volume 204, pages291–295 (2008)Cite this article1.37m Accesses 639 Citations 24 Altmetric MetricsdetailsKey Points Interviews and focus groups are the most common methods of data collection used in qualitative healthcare research Interviews can be used to explore the views, experiences, beliefs and motivations of individual participants Focus group use group dynamics to generate qualitative data Key Points Qualitative research in dentistry 1Qualitative research in dentistry 2Methods of data collection in qualitative research: interviews and focus groups 3Conducting qualitative interviews with school children in dental research 4Analysing and presenting qualitative data Abstract This paper explores the most common methods of data collection used in qualitative research: interviews and focus groups. The paper examines each method in detail, focusing on how they work in practice, when their use is appropriate and what they can offer dentistry. Examples of empirical studies that have used interviews or focus groups are also provided. Introduction Having explored the nature and purpose of qualitative research in the previous paper, this paper explores methods of data collection used in qualitative research. There are a variety of methods of data collection in qualitative research, including observations, textual or visual analysis (eg from books or videos) and interviews (individual or group).

1 However, the most common methods used, particularly in healthcare research, are interviews and focus groups.

2,3The purpose of this paper is to explore these two methods in more detail, in particular how they work in practice, the purpose of each, when their use is appropriate and what they can offer dental research. Qualitative research interviews There are three fundamental types of research interviews: structured, semi-structured and unstructured. Structured interviews are, essentially, verbally administered questionnaires, in which a list of predetermined questions are asked, with little or no variation and with no scope for follow-up questions to responses that warrant further elaboration. Consequently, they are relatively quick and easy to administer and may be of particular use if clarification of certain questions are required or if there are likely to be literacy or numeracy problems with the respondents. However, by their very nature, they only allow for limited participant responses and are, therefore, of little use if 'depth' is required.

Conversely, unstructured interviews do not reflect any preconceived theories or ideas and are performed with little or no organisation.

4 Such an interview may simply start with an opening question such as 'Can you tell me about your experience of visiting the dentist?' and will then progress based, primarily, upon the initial response. Unstructured interviews are usually very time-consuming (often lasting several hours) and can be difficult to manage, and to participate in, as the lack of predetermined interview questions provides little guidance on what to talk about (which many participants find confusing and unhelpful). Their use is, therefore, generally only considered where significant 'depth' is required, or where virtually nothing is known about the subject area (or a different perspective of a known subject area is required).Semi-structured interviews consist of several key questions that help to define the areas to be explored, but also allows the interviewer or interviewee to diverge in order to pursue an idea or response in more detail. 2 This interview format is used most frequently in healthcare, as it provides participants with some guidance on what to talk about, which many find helpful. The flexibility of this approach, particularly compared to structured interviews, also allows for the discovery or elaboration of information that is important to participants but may not have previously been thought of as pertinent by the research team.

For example, in a recent dental public heath study, 5 school children in Cardiff, UK were interviewed about their food choices and preferences. A key finding that emerged from semi-structured interviews, which was not previously thought to be as highly influential as the data subsequently confirmed, was the significance of peer-pressure in influencing children's food choices and preferences. This finding was also established primarily through follow-up questioning (eg probing interesting responses with follow-up questions, such as 'Can you tell me a bit more about that?') and, therefore, may not have emerged in the same way, if at all, if asked as a predetermined question.

The purpose of research interviews The purpose of the research interview is to explore the views, experiences, beliefs and/or motivations of individuals on specific matters (eg factors that influence their attendance at the dentist). Qualitative methods, such as interviews, are believed to provide a 'deeper' understanding of social phenomena than would be obtained from purely quantitative methods, such as questionnaires.1 Interviews are, therefore, most appropriate where little is already known about the study phenomenon or where detailed insights are required from individual participants. They are also particularly appropriate for exploring sensitive topics, where participants may not want to talk about such issues in a group environment.

Examples of dental studies that have collected data using interviews are 'Examining the psychosocial process involved in regular dental attendance'6 and 'Exploring factors governing dentists' treatment philosophies'.7 Gibson et al.6 provided an improved understanding of factors that influenced people's regular attendance with their dentist. The study by Kay and Blinkhorn7 provided a detailed insight into factors that influenced GDPs' decision making in relation to treatment choices. The study found that dentists' clinical decisions about treatments were not necessarily related to pathology or treatment options, as was perhaps initially thought, but also involved discussions with patients, patients' values and dentists' feelings of self esteem and conscience.

There are many similarities between clinical encounters and research interviews, in that both employ similar interpersonal skills, such as questioning, conversing and listening. However, there are also some fundamental differences between the two, such as the purpose of the encounter, reasons for participating, roles of the people involved and how the interview is conducted and recorded.8The primary purpose of clinical encounters is for the dentist to ask the patient questions in order to acquire sufficient information to inform decision making and treatment options. However, the constraints of most consultations are such that any open-ended questioning needs to be brought to a conclusion within a fairly short time.2 In contrast, the fundamental purpose of the research interview is to listen attentively to what respondents have to say, in order to acquire more knowledge about the study topic.9 Unlike the clinical encounter, it is not to intentionally offer any form of help or advice, which many researchers have neither the training nor the time for. Research interviewing therefore requires a different approach and a different range of skills.

The interview When designing an interview schedule it is imperative to ask questions that are likely to yield as much information about the study phenomenon as possible and also be able to address the aims and objectives of the research. In a qualitative interview, good questions should be open-ended (ie, require more than a yes/no answer), neutral, sensitive and understandable.2 It is usually best to start with questions that participants can answer easily and then proceed to more difficult or sensitive topics.2 This can help put respondents at ease, build up confidence and rapport and often generates rich data that subsequently develops the interview further.

As in any research, it is often wise to first pilot the interview schedule on several respondents prior to data collection proper.8 This allows the research team to establish if the schedule is clear, understandable and capable of answering the research questions, and if, therefore, any changes to the interview schedule are required.

The length of interviews varies depending on the topic, researcher and participant. However, on average, healthcare interviews last 20-60 minutes. Interviews can be performed on a one-off or, if change over time is of interest, repeated basis,4 for example exploring the psychosocial impact of oral trauma on participants and their subsequent experiences of cosmetic dental surgery.

Developing the interview Before an interview takes place, respondents should be informed about the study details and given assurance about ethical principles, such as anonymity and confidentiality.2 This gives respondents some idea of what to expect from the interview, increases the likelihood of honesty and is also a fundamental aspect of the informed consent process.

Wherever possible, interviews should be conducted in areas free from distractions and at times and locations that are most suitable for participants. For many this may be at their own home in the evenings. Whilst researchers may have less control over the home environment, familiarity may help the respondent to relax and result in a more productive interview.9 Establishing rapport with participants prior to the interview is also important as this can also have a positive effect on the subsequent development of the interview.

When conducting the actual interview it is prudent for the interviewer to familiarise themselves with the interview schedule, so that the process appears more natural and less rehearsed. However, to ensure that the interview is as productive as possible, researchers must possess a repertoire of skills and techniques to ensure that comprehensive and representative data are collected during the interview.10 One of the most important skills is the ability to listen attentively to what is being said, so that participants are able to recount their experiences as fully as possible, without unnecessary interruptions.

Other important skills include adopting open and emotionally neutral body language, nodding, smiling, looking interested and making encouraging noises (eg, 'Mmmm') during the interview.2 The strategic use of silence, if used appropriately, can also be highly effective at getting respondents to contemplate their responses, talk more, elaborate or clarify particular issues. Other techniques that can be used to develop the interview further include reflecting on remarks made by participants (eg, 'Pain?') and probing remarks ('When you said you were afraid of going to the dentist what did you mean?').9 Where appropriate, it is also wise to seek clarification from respondents if it is unclear what they mean. The use of 'leading' or 'loaded' questions that may unduly influence responses should always be avoided (eg, 'So you think dental surgery waiting rooms are frightening?' rather than 'How do you find the waiting room at the dentists?').At the end of the interview it is important to thank participants for their time and ask them if there is anything they would like to add. This gives respondents an opportunity to deal with issues that they have thought about, or think are important but have not been dealt with by the interviewer.9 This can often lead to the discovery of new, unanticipated information. Respondents should also be debriefed about the study after the interview has finished.All interviews should be tape recorded and transcribed verbatim afterwards, as this protects against bias and provides a permanent record of what was and was not said.8 It is often also helpful to make 'field notes' during and immediately after each interview about observations, thoughts and ideas about the interview, as this can help in data analysis process.4,8 Focus groups Focus groups share many common features with less structured interviews, but there is more to them than merely collecting similar data from many participants at once. A focus group is a group discussion on a particular topic organised for research purposes. This discussion is guided, monitored and recorded by a researcher (sometimes called a moderator or facilitator).11,12Focus groups were first used as a research method in market research, originating in the 1940s in the work of the Bureau of Applied Social Research at Columbia University. Eventually the success of focus groups as a marketing tool in the private sector resulted in its use in public sector marketing, such as the assessment of the impact of health education campaigns.13 However, focus group techniques, as used in public and private sectors, have diverged over time. Therefore, in this paper, we seek to describe focus groups as they are used in academic research.

When focus groups are used Focus groups are used for generating information on collective views, and the meanings that lie behind those views. They are also useful in generating a rich understanding of participants' experiences and beliefs.12 Suggested criteria for using focus groups include:13 As a standalone method, for research relating to group norms, meanings and processes In a multi-method design, to explore a topic or collect group language or narratives to be used in later stages To clarify, extend, qualify or challenge data collected through other methods To feedback results to research participants.Morgan12 suggests that focus groups should be avoided according to the following criteria: If listening to participants' views generates expectations for the outcome of the research that can not be fulfilled If participants are uneasy with each other, and will therefore not discuss their feelings and opinions openly If the topic of interest to the researcher is not a topic the participants can or wish to discuss If statistical data is required. Focus groups give depth and insight, but cannot produce useful numerical results.

Conducting focus groups: group composition and size The composition of a focus group needs great care to get the best quality of discussion. There is no 'best' solution to group composition, and group mix will always impact on the data, according to things such as the mix of ages, sexes and social professional statuses of the participants. What is important is that the researcher gives due consideration to the impact of group mix (eg, how the group may interact with each other) before the focus group proceeds.14Interaction is key to a successful focus group. Sometimes this means a pre-existing group interacts best for research purposes, and sometimes stranger groups. Pre-existing groups may be easier to recruit, have shared experiences and enjoy a comfort and familiarity which facilitates discussion or the ability to challenge each other comfortably. In health settings, pre-existing groups can overcome issues relating to disclosure of potentially stigmatising status which people may find uncomfortable in stranger groups (conversely there may be situations where disclosure is more comfortable in stranger groups). In other research projects it may be decided that stranger groups will be able to speak more freely without fear of repercussion, and challenges to other participants may be more challenging and probing, leading to richer data.13Group size is an important consideration in focus group research. Stewart and Shamdasani14 suggest that it is better to slightly over-recruit for a focus group and potentially manage a slightly larger group, than under-recruit and risk having to cancel the session or having an unsatisfactory discussion. They advise that each group will probably have two non-attenders. The optimum size for a focus group is six to eight participants (excluding researchers), but focus groups can work successfully with as few as three and as many as 14 participants. Small groups risk limited discussion occurring, while large groups can be chaotic, hard to manage for the moderator and frustrating for participants who feel they get insufficient opportunities to speak.13Preparing an interview schedule Like research interviews, the interview schedule for focus groups is often no more structured than a loose schedule of topics to be discussed. However, in preparing an interview schedule for focus groups, Stewart and Shamdasani14 suggest two general principles: 1Questions should move from general to more specific questions 2Question order should be relative to importance of issues in the research agenda.

There can, however, be some conflict between these two principles, and trade offs are often needed, although often discussions will take on a life of their own, which will influence or determine the order in which issues are covered. Usually, less than a dozen predetermined questions are needed and, as with research interviews, the researcher will also probe and expand on issues according to the discussion.Moderating Moderating a focus group looks easy when done well, but requires a complex set of skills, which are related to the following principles:15 Participants have valuable views and the ability to respond actively, positively and respectfully. Such an approach is not simply a courtesy, but will encourage fruitful discussions Moderating without participating: a moderator must guide a discussion rather than join in with it. Expressing one's own views tends to give participants cues as to what to say (introducing bias), rather than the confidence to be open and honest about their own views Be prepared for views that may be unpalatably critical of a topic which may be important to you It is important to recognise that researchers' individual characteristics mean that no one person will always be suitable to moderate any kind of group. Sometimes the characteristics that suit a moderator for one group will inhibit discussion in another Be yourself. If the moderator is comfortable and natural, participants will feel relaxed.

The moderator should facilitate group discussion, keeping it focussed without leading it. They should also be able to prevent the discussion being dominated by one member (for example, by emphasising at the outset the importance of hearing a range of views), ensure that all participants have ample opportunity to contribute, allow differences of opinions to be discussed fairly and, if required, encourage reticent participants.13Other relevant factors The venue for a focus group is important and should, ideally, be accessible, comfortable, private, quiet and free from distractions.13 However, while a central location, such as the participants' workplace or school, may encourage attendance, the venue may affect participants' behaviour. For example, in a school setting, pupils may behave like pupils, and in clinical settings, participants may be affected by any anxieties that affect them when they attend in a patient role.

Focus groups are usually recorded, often observed (by a researcher other than the moderator, whose role is to observe the interaction of the group to enhance analysis) and sometimes videotaped. At the start of a focus group, a moderator should acknowledge the presence of the audio recording equipment, assure participants of confidentiality and give people the opportunity to withdraw if they are uncomfortable with being taped.14A good quality multi-directional external microphone is recommended for the recording of focus groups, as internal microphones are rarely good enough to cope with the variation in volume of different speakers.13 If observers are present, they should be introduced to participants as someone who is just there to observe, and sit away from the discussion.14 Videotaping will require more than one camera to capture the whole group, as well as additional operational personnel in the room. This is, therefore, very obtrusive, which can affect the spontaneity of the group and in a focus group does not usually yield enough additional information that could not be captured by an observer to make videotaping worthwhile.15The systematic analysis of focus group transcripts is crucial. However, the transcription of focus groups is more complex and time consuming than in one-to-one interviews, and each hour of audio can take up to eight hours to transcribe and generate approximately 100 pages of text. Recordings should be transcribed verbatim and also speakers should be identified in a way that makes it possible to follow the contributions of each individual. Sometimes observational notes also need to be described in the transcripts in order for them to make sense.

The analysis of qualitative data is explored in the final paper of this series. However, it is important to note that the analysis of focus group data is different from other qualitative data because of their interactive nature, and this needs to be taken into consideration during analysis. The importance of the context of other speakers is essential to the understanding of individual contributions.13 For example, in a group situation, participants will often challenge each other and justify their remarks because of the group setting, in a way that perhaps they would not in a one-to-one interview. The analysis of focus group data must therefore take account of the group dynamics that have generated remarks.

Focus groups in dental research Focus groups are used increasingly in dental research, on a diverse range of topics,16 illuminating a number of areas relating to patients, dental services and the dental profession. Addressing a special needs population difficult to access and sample through quantitative measures, Robinson et al.17 used focus groups to investigate the oral health-related attitudes of drug users, exploring the priorities, understandings and barriers to care they encounter. Newton et al.18 used focus groups to explore barriers to services among minority ethnic groups, highlighting for the first time differences between minority ethnic groups. Demonstrating the use of the method with professional groups as subjects in dental research, Gussy et al.19 explored the barriers to and possible strategies for developing a shared approach in prevention of caries among pre-schoolers. This mixed method study was very important as the qualitative element was able to explain why the clinical trial failed, and this understanding may help researchers improve on the quantitative aspect of future studies, as well as making a valuable academic contribution in its own right. Conclusion Interviews and focus groups remain the most common methods of data collection in qualitative research, and are now being used with increasing frequency in dental research, particularly to access areas not amendable to quantitative methods and/or where depth, insight and understanding of particular phenomena are required. The examples of dental studies that have employed these methods also help to demonstrate the range of research contexts to which interview and focus group research can make a useful contribution. The continued employment of these methods can further strengthen many areas of dentally related work.

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Focus groups in social research. London: Sage Publications, 2001.Book Google Scholar 14Stewart D W, Shamdasani P M . Focus groups. Theory and practice. London: Sage Publications, 1990.Google Scholar 15Krueger R A . Moderating focus groups. London: Sage Publications, 1998.Book Google Scholar 16Chestnutt I G, Robson K F. Focus groups – what are they? Dent Update 2002; 28: 189–192.Article Google Scholar 17Robinson P G, Acquah S, Gibson B . Drug users: oral health related attitudes and behaviours. Br Dent J 2005; 198: 219–224.Article Google Scholar 18Newton J T, Thorogood N, Bhavnani V, Pitt J, Gibbons D E, Gelbier S . Barriers to the use of dental services by individuals from minority ethnic communities living in the United Kingdom: findings from focus groups. Primary Dent Care 2001; 8: 157–161.Article Google Scholar 19Gussy M G, Waters E, Kilpatrick M . A qualitative study exploring barriers to a model of shared care for pre-school children's oral health. Br Dent J 2006; 201: 165–170.Article Google ScholarDownload references Author information Affiliations Senior Research Fellow, Faculty of Health, Sport and Science, University of Glamorgan, Pontypridd, CF37 1DLP. Gill Research Fellow, Academic Unit of Primary Care, University of Bristol, Bristol, BS8 2AAK. Stewart Dean and Professor of Dental Public Health, School of Dentistry, Dental Health and Biological Sciences, School of Dentistry, Cardiff University, Heath Park, Cardiff, CF14 4XYE. Treasure Professor of Paediatric Dentistry, School of Dentistry, Dental Health and Biological Sciences, School of Dentistry, Cardiff University, Heath Park, Cardiff, CF14 4XYB. ChadwickCorresponding author Correspondence to P. Gill. Additional information Refereed paper Rights and permissions Reprints and Permissions About this article Cite this article Gill, P., Stewart, K., Treasure, E. et al. Methods of data collection in qualitative research: interviews and focus groups. Br Dent J 204, 291–295 (2008). https://doi.org/10.1038/bdj.2008.192Download citation Published22 March 2008 Issue Date22 March 2008 DOIhttps://doi.org/10.1038/bdj.2008.192 Further reading ‘Don’t forget the mouth!’: a process evaluation of a public oral health project in community-dwelling frail older people Bach Van Ho Claar Debora van der Maarel-Wierink Frank Lobbezoo BMC Oral Health (2021) Opioid use disorder in pregnancy: leveraging provider perceptions to inform comprehensive treatment Doris Titus-Glover Fadia T. Shaya Rebecca Vivrette BMC Health Services Research (2021) Conducting household surveys on reproductive health in urban settings: lessons from Karachi, Pakistan Mir Baz Khan Sidrah Nausheen Sajid Bashir Soofi BMC Medical Research Methodology (2021) A qualitative exploration of the unmet information needs of Chinese advanced cancer patients and their informal caregivers Tao Wang Alex Molassiotis Jing-Yu Tan BMC Palliative Care (2021) Protocol for a multi-phase, mixed methods study to develop and evaluate culturally adapted CBT to improve community mental health services for Canadians of south Asian origin Farooq Naeem Andrew Tuck Kwame McKenzie Trials (2021)

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British Dental Journal (Br Dent J) ISSN 1476-5373 (online) ISSN 0007-0610 (print)"

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Hi Sameera,First of all, tell me what is the purpose, hypothesis and research question of this study? The analysis of data always has to be done keeping in mind the research objective.

Bonjour Samerra,

Certains chercheurs définissent la recherche qualitative comme l’ensemble des approches utilisées pour explorer et pour comprendre en profondeur les expériences humaines, les perceptions et les comportements (Parahoo, 2006). Au cours des dernières années, la recherche qualitative a acquis une visibilité et une légitimité plus grande dans le domaine des sciences humaines et notamment en ce qui concerne la psychologie et les sciences de l’éducation (Hébert & al., 1997).

La valeur d’une recherche qualitative repose en grande partie sur la capacité du chercheur à donner un sens aux données (Savoie-Zajc, 2000). En effet, l'analyse de contenu est une technique qui permet de prendre connaissance des thèmes explicites ou implicites dans un texte à partir d'une pré-lecture, dans un premier temps, et d'une lecture approfondie, dans un deuxième temps. Il s’agit « d’une technique de recherche pour la description objective, systématique et quantitative du contenu manifeste des communications ayant pour but de les interpréter » (Evrad & al., 1987, p.116). Elle permet, donc, « de découvrir, par une méthode rigoureuse d’analyse des textes, la signification des messages contenus dans le matériel. La mise en relation des textes permet de mesurer la complexité du phénomène étudié et de dégager une vue d’ensemble de celui-ci » (Richard, 2006, p.184).

Par ailleurs, « l’analyse de contenu s’organise autour de trois phases chronologiques : la pré-analyse, l’exploitation du matériel ainsi que le traitement des résultats, l’inférence et l’interprétation. Pour commencer, la pré-analyse, appelée par Bardin (2001) « lecture flottante », est « l’étape préliminaire d’intuition et d’organisation pour opérationnaliser et systématiser les idées de départ afin d’aboutir à un schéma ou à un plan d’analyse » (Wanlin, 2007, p.249). Cette phase a trois missions : le choix des documents à soumettre à l’analyse, la formulation des hypothèses et des objectifs et l’élaboration des indicateurs sur lesquels s’appuiera l’interprétation finale. Pour continuer, le traitement des résultats est la seconde phase. Elle doit être élaborée de manière à être significative et valide. Pour terminer, l’interprétation des résultats permet d’une part d’évaluer la fécondité du dispositif et d’autre part, d’évaluer la valeur des hypothèses.

Il faut souligner que sous le couvert de l’appellation « analyse de contenu », existent bon nombre de méthodes différentes, issues de divers courants et aboutissant à des résultats spécifiques à la méthode employée. En effet, le choix dépend du but visé par le chercheur ainsi que le type de résultats visés.